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State-space representation

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307:, is usually equal to the order of the system's defining differential equation, but not necessarily. If the system is represented in transfer function form, the minimum number of state variables is equal to the order of the transfer function's denominator after it has been reduced to a proper fraction. It is important to understand that converting a state-space realization to a transfer function form may lose some internal information about the system, and may provide a description of a system which is stable, when the state-space realization is unstable at certain points. In electric circuits, the number of state variables is often, though not always, the same as the number of energy storage elements in the circuit such as 6013: 36: 324: 9142: 12530: 8530: 12510: 9572: 8890: 5255: 4840: 8267: 10764: 9365: 9137:{\displaystyle {\begin{bmatrix}B&AB\end{bmatrix}}={\begin{bmatrix}{\begin{bmatrix}0\\{\frac {1}{m}}\end{bmatrix}}&{\begin{bmatrix}0&1\\-{\frac {k}{m}}&-{\frac {b}{m}}\end{bmatrix}}{\begin{bmatrix}0\\{\frac {1}{m}}\end{bmatrix}}\end{bmatrix}}={\begin{bmatrix}0&{\frac {1}{m}}\\{\frac {1}{m}}&-{\frac {b}{m^{2}}}\end{bmatrix}}} 3098: 4974: 4008: 4591: 8525:{\displaystyle {\begin{bmatrix}{\dot {\mathbf {x} }}_{1}(t)\\{\dot {\mathbf {x} }}_{2}(t)\end{bmatrix}}={\begin{bmatrix}0&1\\-{\frac {k}{m}}&-{\frac {b}{m}}\end{bmatrix}}{\begin{bmatrix}\mathbf {x} _{1}(t)\\\mathbf {x} _{2}(t)\end{bmatrix}}+{\begin{bmatrix}0\\{\frac {1}{m}}\end{bmatrix}}\mathbf {u} (t)} 10494: 3125:
Observability is a measure for how well internal states of a system can be inferred by knowledge of its external outputs. The observability and controllability of a system are mathematical duals (i.e., as controllability provides that an input is available that brings any initial state to any desired
5849: 7631: 3235: 3717: 9567:{\displaystyle {\begin{bmatrix}C\\CA\end{bmatrix}}={\begin{bmatrix}{\begin{bmatrix}1&0\end{bmatrix}}\\{\begin{bmatrix}1&0\end{bmatrix}}{\begin{bmatrix}0&1\\-{\frac {k}{m}}&-{\frac {b}{m}}\end{bmatrix}}\end{bmatrix}}={\begin{bmatrix}1&0\\0&1\end{bmatrix}}} 5966: 4580: 5250:{\displaystyle {\dot {\textbf {x}}}(t)={\begin{bmatrix}0&0&0&-d_{4}\\1&0&0&-d_{3}\\0&1&0&-d_{2}\\0&0&1&-d_{1}\end{bmatrix}}{\textbf {x}}(t)+{\begin{bmatrix}n_{4}\\n_{3}\\n_{2}\\n_{1}\end{bmatrix}}{\textbf {u}}(t)} 2989: 4956: 3843: 134:, evolve over time in a way that depends on the values they have at any given instant and on the externally imposed values of input variables. Output variables’ values depend on the state variable values and may also depend on the input variable values. 2770: 7767: 2976:
The state controllability condition implies that it is possible â€“ by admissible inputs â€“ to steer the states from any initial value to any final value within some finite time window. A continuous time-invariant linear state-space model is
3445: 2444: 2260: 3574: 4282: 1701: 494: 4835:{\displaystyle {\dot {\mathbf {x} }}(t)={\begin{bmatrix}0&1&0&0\\0&0&1&0\\0&0&0&1\\-d_{4}&-d_{3}&-d_{2}&-d_{1}\end{bmatrix}}\mathbf {x} (t)+{\begin{bmatrix}0\\0\\0\\1\end{bmatrix}}\mathbf {u} (t)} 5347: 10296: 10902: 9951: 6551: 3341: 1518: 2061: 5697: 2154: 1794: 588: 7311: 10759:{\displaystyle {\dot {\mathbf {x} }}(t)={\begin{bmatrix}{\dot {x}}_{1}(t)\\{\dot {x}}_{2}(t)\end{bmatrix}}=\mathbf {f} (t,x(t))={\begin{bmatrix}x_{2}(t)\\-{\frac {g}{\ell }}\sin {x_{1}}(t)-{\frac {k}{m\ell }}{x_{2}}(t)\end{bmatrix}}.} 7879: 5459: 1881: 3832: 2519: 2335: 1956: 1593: 5708: 7406: 7448: 3139: 6325: 7130: 6164: 6850: 6942: 1286: 5530: 6635: 4345:
which contains transfer functions for each input output combination. Due to the simplicity of this matrix notation, the state-space representation is commonly used for multiple-input, multiple-output systems. The
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into trend and cycle, compose individual indicators into a composite index, identify turning points of the business cycle, and estimate GDP using latent and unobserved time series. Many applications rely on the
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are the smallest possible subset of system variables that can represent the entire state of the system at any given time. The minimum number of state variables required to represent a given system,
8840: 829: 750: 671: 7931: 6073: 3093:{\displaystyle \operatorname {rank} {\begin{bmatrix}\mathbf {B} &\mathbf {A} \mathbf {B} &\mathbf {A} ^{2}\mathbf {B} &\cdots &\mathbf {A} ^{n-1}\mathbf {B} \end{bmatrix}}=n,} 6899: 5464:
The strictly proper transfer function can then be transformed into a canonical state-space realization using techniques shown above. The state-space realization of the constant is trivially
4381: 10482: 4050: 11043: 10422: 10168: 8762: 8651: 2814: 315:. The state variables defined must be linearly independent, i.e., no state variable can be written as a linear combination of the other state variables, or the system cannot be solved. 4003:{\displaystyle \mathbf {Y} (s)=\mathbf {C} ((s\mathbf {I} -\mathbf {A} )^{-1}\mathbf {x} (0)+(s\mathbf {I} -\mathbf {A} )^{-1}\mathbf {B} \mathbf {U} (s))+\mathbf {D} \mathbf {U} (s).} 4848: 9794: 6002: 2571: 7637: 1157: 1126: 1038: 950: 862: 783: 704: 625: 10353: 1370: 1342: 3352: 2941: 2351: 8874: 7440: 6434: 4317: 3751: 3479: 2170: 9290: 8158: 4119: 3487: 1416:
allow for time domains that have both continuous and discrete parts. Depending on the assumptions made, the state-space model representation can assume the following forms:
1212: 1093: 1005: 917: 9252: 8120: 4203: 1604: 397: 10810: 2559: 12404: 9986: 5263: 10174: 4343: 250: 10818: 8693: 2958:) even though it is not internally stable. This may be the case if unstable poles are canceled out by zeros (i.e., if those singularities in the transfer function are 9842: 6442: 3262: 1439: 1967: 11325: 10074: 9823: 9214: 8189: 8082: 6976: 6931: 5557: 2066: 1706: 500: 7213: 5356:
because the resulting model is guaranteed to be observable (i.e., because the output exits from a chain of integrators, every state has an effect on the output).
182:. The capacity of these structures can be efficiently applied to research systems with or without modulation. The state-space representation (also known as the " 7782: 10094: 10052: 10030: 10008: 9350: 9330: 9310: 9185: 9165: 8255: 8233: 8211: 4965:
because the resulting model is guaranteed to be controllable (i.e., because the control enters a chain of integrators, it has the ability to move every state).
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Stock, J.H.; Watson, M.W. (2016), "Dynamic Factor Models, Factor-Augmented Vector Autoregressions, and Structural Vector Autoregressions in Macroeconomics",
5844:{\displaystyle {\dot {\textbf {x}}}(t)={\begin{bmatrix}-2&-1\\1&0\\\end{bmatrix}}{\textbf {x}}(t)+{\begin{bmatrix}1\\0\end{bmatrix}}{\textbf {u}}(t)} 2449: 2265: 1886: 1523: 7317: 7626:{\displaystyle {\dot {\mathbf {x} }}(t)=\left(A-BK\left(I+DK\right)^{-1}C\right)\mathbf {x} (t)+B\left(I-K\left(I+DK\right)^{-1}D\right)\mathbf {r} (t)} 11652: 3230:{\displaystyle \operatorname {rank} {\begin{bmatrix}\mathbf {C} \\\mathbf {C} \mathbf {A} \\\vdots \\\mathbf {C} \mathbf {A} ^{n-1}\end{bmatrix}}=n.} 11239:
Bańbura, Marta; Modugno, Michele (2012-11-12). "Maximum Likelihood Estimation of Factor Models on Datasets with Arbitrary Pattern of Missing Data".
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The state-space model can be applied in subjects such as economics, statistics, computer science and electrical engineering, and neuroscience. In
6247: 5372:) can also be realised quite easily. The trick here is to separate the transfer function into two parts: a strictly proper part and a constant. 4375:
Given a transfer function, expand it to reveal all coefficients in both the numerator and denominator. This should result in the following form:
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can easily be transferred into state-space by the following approach (this example is for a 4-dimensional, single-input, single-output system):
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final state, observability provides that knowing an output trajectory provides enough information to predict the initial state of the system).
3712:{\displaystyle \mathbf {X} (s)=(s\mathbf {I} -\mathbf {A} )^{-1}\mathbf {x} (0)+(s\mathbf {I} -\mathbf {A} )^{-1}\mathbf {B} \mathbf {U} (s).} 1219: 5467: 6557: 1292:
In this general formulation, all matrices are allowed to be time-variant (i.e. their elements can depend on time); however, in the common
6331: 7136: 6981: 6170: 17: 9591: 5961:{\displaystyle {\textbf {y}}(t)={\begin{bmatrix}1&2\end{bmatrix}}{\textbf {x}}(t)+{\begin{bmatrix}1\end{bmatrix}}{\textbf {u}}(t)} 6083:. The presence of a negative sign (the common notation) is merely a notational one and its absence has no impact on the end results. 4135: 259:
approach, the use of the state-space representation is not limited to systems with linear components and zero initial conditions.
11762: 11645: 11506: 9677: 7951: 2903:. An alternative approach to determining stability, which does not involve calculating eigenvalues, is to analyze the system's 2822: 6655: 11594: 11564: 11495: 11438: 11393: 11309: 11116: 11092: 11026: 10999: 12435: 11229:," NBER Chapters, in: NBER Macroeconomics Annual 1989, Volume 4, pages 351-409, National Bureau of Economic Research, Inc. 8769: 12536: 12087: 11824: 788: 709: 630: 4575:{\displaystyle {\textbf {G}}(s)={\frac {n_{1}s^{3}+n_{2}s^{2}+n_{3}s+n_{4}}{s^{4}+d_{1}s^{3}+d_{2}s^{2}+d_{3}s+d_{4}}}.} 7885: 6027: 12564: 12348: 11975: 11782: 11638: 11545: 11519: 11476: 11457: 6856: 4053: 186:
approach") provides a convenient and compact way to model and analyze systems with multiple inputs and outputs. With
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or a state observer to produce estimates of the current unknown state variables using their previous observations.
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is a linear combination of states and inputs then the equations can be written in matrix notation like above. The
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is the "feedthrough (or feedforward) matrix" (in cases where the system model does not have a direct feedthrough,
4951:{\displaystyle \mathbf {y} (t)={\begin{bmatrix}n_{4}&n_{3}&n_{2}&n_{1}\end{bmatrix}}\mathbf {x} (t).} 10360: 10106: 8700: 8536: 2895:
where the transfer function's magnitude is unbounded). These poles can be used to analyze whether the system is
2786: 12569: 12490: 12430: 12028: 2765:{\displaystyle {\textbf {G}}(s)=k{\frac {(s-z_{1})(s-z_{2})(s-z_{3})}{(s-p_{1})(s-p_{2})(s-p_{3})(s-p_{4})}}.} 12574: 12023: 11712: 9758: 7762:{\displaystyle \mathbf {y} (t)=\left(I+DK\right)^{-1}C\mathbf {x} (t)+\left(I+DK\right)^{-1}D\mathbf {r} (t)} 97: 5974: 12465: 11862: 11819: 11772: 11767: 11624: 11175:
Smith, Anne C.; Brown, Emery N. (2003). "Estimating a State-Space Model from Point Process Observations".
1131: 1100: 1012: 924: 836: 757: 678: 599: 12579: 12516: 11812: 11738: 10307: 3440:{\displaystyle s\mathbf {X} (s)-\mathbf {x} (0)=\mathbf {A} \mathbf {X} (s)+\mathbf {B} \mathbf {U} (s).} 2439:{\displaystyle z\mathbf {X} (z)-z\mathbf {x} (0)=\mathbf {A} \mathbf {X} (z)+\mathbf {B} \mathbf {U} (z)} 2255:{\displaystyle s\mathbf {X} (s)-\mathbf {x} (0)=\mathbf {A} \mathbf {X} (s)+\mathbf {B} \mathbf {U} (s)} 12140: 12075: 11676: 11620: 7942: 3569:{\displaystyle (s\mathbf {I} -\mathbf {A} )\mathbf {X} (s)=\mathbf {x} (0)+\mathbf {B} \mathbf {U} (s)} 1347: 1319: 4277:{\displaystyle \mathbf {G} (s)=\mathbf {C} (s\mathbf {I} -\mathbf {A} )^{-1}\mathbf {B} +\mathbf {D} } 2913: 1696:{\displaystyle {\dot {\mathbf {x} }}(t)=\mathbf {A} (t)\mathbf {x} (t)+\mathbf {B} (t)\mathbf {u} (t)} 489:{\displaystyle {\dot {\mathbf {x} }}(t)=\mathbf {A} (t)\mathbf {x} (t)+\mathbf {B} (t)\mathbf {u} (t)} 12541: 12399: 12038: 11869: 11692: 8848: 7414: 6408: 4291: 3725: 3453: 2776: 9257: 8125: 6941: 4585:
The coefficients can now be inserted directly into the state-space model by the following approach:
4063: 1162: 1043: 955: 867: 12440: 11697: 9219: 8087: 5365: 5342:{\displaystyle {\textbf {y}}(t)={\begin{bmatrix}0&0&0&1\end{bmatrix}}{\textbf {x}}(t).} 4347: 4126: 2892: 2561:. The stability of a time-invariant state-space model can be determined by looking at the system's 44: 10780: 10291:{\displaystyle {\dot {x}}_{2}(t)=-{\frac {g}{\ell }}\sin {x_{1}}(t)-{\frac {k}{m\ell }}{x_{2}}(t)} 2542: 12485: 12470: 12123: 12118: 12018: 11886: 11667: 11616: 10897:{\displaystyle {\begin{bmatrix}x_{1}\\x_{2}\end{bmatrix}}={\begin{bmatrix}n\pi \\0\end{bmatrix}}} 11044:"Modeling of dynamic systems with modulation by means of Kronecker vector-matrix representation" 9962: 9946:{\displaystyle m\ell ^{2}{\ddot {\theta }}(t)=-m\ell g\sin \theta (t)-k\ell {\dot {\theta }}(t)} 6546:{\displaystyle {\dot {\mathbf {x} }}(t)=\left(A+BK\left(I-DK\right)^{-1}C\right)\mathbf {x} (t)} 4968:
The transfer function coefficients can also be used to construct another type of canonical form
3336:{\displaystyle {\dot {\mathbf {x} }}(t)=\mathbf {A} \mathbf {x} (t)+\mathbf {B} \mathbf {u} (t)} 1513:{\displaystyle {\dot {\mathbf {x} }}(t)=\mathbf {A} \mathbf {x} (t)+\mathbf {B} \mathbf {u} (t)} 12445: 12205: 11924: 11919: 10770: 4322: 3249:" of a continuous time-invariant linear state-space model can be derived in the following way: 2056:{\displaystyle \mathbf {x} (k+1)=\mathbf {A} (k)\mathbf {x} (k)+\mathbf {B} (k)\mathbf {u} (k)} 229: 119: 61: 10989: 8662: 12475: 12460: 12425: 12113: 12013: 11881: 11016: 9825:
argument to the functions can be dropped if the system is unforced (i.e., it has no inputs).
5692:{\displaystyle {\textbf {G}}(s)={\frac {s^{2}+3s+3}{s^{2}+2s+1}}={\frac {s+2}{s^{2}+2s+1}}+1} 4363: 3104: 2959: 2896: 2149:{\displaystyle \mathbf {y} (k)=\mathbf {C} (k)\mathbf {x} (k)+\mathbf {D} (k)\mathbf {u} (k)} 1789:{\displaystyle \mathbf {y} (t)=\mathbf {C} (t)\mathbf {x} (t)+\mathbf {D} (t)\mathbf {u} (t)} 583:{\displaystyle \mathbf {y} (t)=\mathbf {C} (t)\mathbf {x} (t)+\mathbf {D} (t)\mathbf {u} (t)} 123: 107: 12343: 7306:{\displaystyle {\dot {\mathbf {x} }}(t)=A\mathbf {x} (t)-BK\mathbf {y} (t)+B\mathbf {r} (t)} 2535:(i.e., linear with matrices that are constant with respect to time) can be studied from the 12495: 12450: 11896: 11841: 11687: 11682: 10059: 7941:
A classical linear system is that of one-dimensional movement of an object (e.g., a cart).
7874:{\displaystyle {\dot {\mathbf {x} }}(t)=\left(A-BKC\right)\mathbf {x} (t)+B\mathbf {r} (t)} 171: 152: 9799: 9190: 8165: 8058: 6952: 6907: 6012: 8: 12070: 12048: 11797: 11792: 11750: 11702: 11060: 10921: 5454:{\displaystyle {\textbf {G}}(s)={\textbf {G}}_{\mathrm {SP} }(s)+{\textbf {G}}(\infty ).} 1876:{\displaystyle \mathbf {x} (k+1)=\mathbf {A} \mathbf {x} (k)+\mathbf {B} \mathbf {u} (k)} 127: 103: 93: 11488:
Mathematical Systems Theory I, Modelling, State Space Analysis, Stability and Robustness
3827:{\displaystyle \mathbf {Y} (s)=\mathbf {C} \mathbf {X} (s)+\mathbf {D} \mathbf {U} (s),} 12455: 12033: 11353: 11274: 11208: 10079: 10037: 10015: 9993: 9755:
The first is the state equation and the latter is the output equation. If the function
9335: 9315: 9295: 9170: 9150: 8240: 8218: 8196: 4125:, however, this ratio is not defined. Therefore, assuming zero initial conditions, the 2904: 2900: 2514:{\displaystyle \mathbf {Y} (z)=\mathbf {C} \mathbf {X} (z)+\mathbf {D} \mathbf {U} (z)} 2330:{\displaystyle \mathbf {Y} (s)=\mathbf {C} \mathbf {X} (s)+\mathbf {D} \mathbf {U} (s)} 1951:{\displaystyle \mathbf {y} (k)=\mathbf {C} \mathbf {x} (k)+\mathbf {D} \mathbf {u} (k)} 1588:{\displaystyle \mathbf {y} (t)=\mathbf {C} \mathbf {x} (t)+\mathbf {D} \mathbf {u} (t)} 1395: 1375: 1299: 374: 354: 334: 290: 209: 189: 167: 115: 9577:
which also has full rank. Therefore, this system is both controllable and observable.
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in which the axes are the state variables. The system state can be represented as a
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for an object moving horizontally on a plane and attached to a wall with a spring:
7401:{\displaystyle \mathbf {y} (t)=C\mathbf {x} (t)-DK\mathbf {y} (t)+D\mathbf {r} (t)} 256: 163: 11084: 11048:
Scientific and Technical Journal of Information Technologies, Mechanics and Optics
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equals zero. Another fairly common situation is when all states are outputs, i.e.
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Roesser, R. (1975). "A discrete state-space model for linear image processing".
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for information about phase state (like state space) in physics and mathematics.
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form. The state-space method is characterized by the algebraization of general
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The more general form of a state-space model can be written as two functions.
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Notice how the output also depends directly on the input. This is due to the
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is linear, time-invariant, and finite-dimensional, then the differential and
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for information about state space with discrete states in computer science.
6320:{\displaystyle {\dot {\mathbf {x} }}(t)=A\mathbf {x} (t)+BK\mathbf {y} (t)} 2888: 263: 7125:{\displaystyle {\dot {\mathbf {x} }}(t)=A\mathbf {x} (t)+B\mathbf {u} (t)} 6159:{\displaystyle {\dot {\mathbf {x} }}(t)=A\mathbf {x} (t)+B\mathbf {u} (t)} 12480: 12251: 12160: 12155: 11777: 11755: 10958: 10952: 6845:{\displaystyle {\dot {\mathbf {x} }}(t)=\left(A+BK\right)\mathbf {x} (t)} 6641: 2780: 267: 183: 143: 11261: 1281:{\displaystyle {\dot {\mathbf {x} }}(t):={\frac {d}{dt}}\mathbf {x} (t)} 12374: 12333: 12328: 12241: 12150: 12058: 11970: 11950: 10010:
is the mass of the pendulum (pendulum rod's mass is assumed to be zero)
5525:{\displaystyle {\textbf {y}}(t)={\textbf {G}}(\infty ){\textbf {u}}(t)} 2884: 2536: 2532: 1293: 11341: 6630:{\displaystyle \mathbf {y} (t)=\left(I-DK\right)^{-1}C\mathbf {x} (t)} 12369: 12338: 12236: 12080: 12043: 11980: 11934: 11929: 11914: 11508:
Mathematical Control Theory: Deterministic Finite Dimensional Systems
11374:. Cambridge: Cambridge University Press. doi:10.1017/CBO9781107049994 11252: 9988:
is the angle of the pendulum with respect to the direction of gravity
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is the radius of the pendulum (to the center of gravity of the mass
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Stability and natural response characteristics of a continuous-time
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The most general state-space representation of a linear system with
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and so the equilibrium points of a pendulum are those that satisfy
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A common method for feedback is to multiply the output by a matrix
2341: 312: 6395:{\displaystyle \mathbf {y} (t)=C\mathbf {x} (t)+DK\mathbf {y} (t)} 3107:
is the number of linearly independent rows in a matrix, and where
12394: 12231: 12185: 12108: 12008: 12003: 11955: 7197:{\displaystyle \mathbf {y} (t)=C\mathbf {x} (t)+D\mathbf {u} (t)} 7042:{\displaystyle \mathbf {u} (t)=-K\mathbf {y} (t)+\mathbf {r} (t)} 6231:{\displaystyle \mathbf {y} (t)=C\mathbf {x} (t)+D\mathbf {u} (t)} 4350:
provides a bridge between the state-space representation and its
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Forecasting, Structural Time Series Models and the Kalman Filter
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Katalin M. Hangos; József Bokor & Gábor Szederkényi (2004).
9666:{\displaystyle \mathbf {\dot {x}} (t)=\mathbf {f} (t,x(t),u(t))} 9352:
that could move the cart into any other position in the system.
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Block diagram representation of the linear state-space equations
12409: 12389: 12261: 12053: 11292:"State-Space Models with Markov Switching and Gibbs-Sampling", 10488:
Instead, the state equation can be written in the general form
5532:. Together we then get a state-space realization with matrices 4187:{\displaystyle \mathbf {Y} (s)=\mathbf {G} (s)\mathbf {U} (s)} 118:
of a physical system specified as a set of input, output, and
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Control System Design: An Introduction to State-Space Methods
266:, for example, state-space models can be used to decompose a 11326:"A New Approach to Linear Filtering and Prediction Problems" 9187:. This means, that if initial state of the system is known ( 7772:
One fairly common simplification to this system is removing
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using the method of equating the coefficients which yields
4122: 11227:"New Indexes of Coincident and Leading Economic Indicators 10991:
Intelligent Control Systems: An Introduction with Examples
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On the applications of state-space models in econometrics
11041: 9745:{\displaystyle \mathbf {y} (t)=\mathbf {h} (t,x(t),u(t))} 8042:{\displaystyle m{\ddot {y}}(t)=u(t)-b{\dot {y}}(t)-ky(t)} 2981: 2943:
can similarly be used to determine whether the system is
2873:{\displaystyle \lambda (s)=|s\mathbf {I} -\mathbf {A} |.} 2775:
The denominator of the transfer function is equal to the
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in factored form. It will then look something like this:
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case, matrices will be time invariant. The time variable
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to encode all the information about a system. Unlike the
6719:{\displaystyle \left(A+BK\left(I-DK\right)^{-1}C\right)} 3129:
A continuous time-invariant linear state-space model is
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This reduces the necessary eigendecomposition to just
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are unrestricted the values can easily be negated for
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Hinrichsen, Diederich; Pritchard, Anthony J. (2005).
11413:(1st ed.). Quantum Publishers, Inc. p. 172. 10821: 10783: 10497: 10432: 10363: 10310: 10177: 10109: 10082: 10062: 10040: 10018: 9996: 9965: 9845: 9802: 9761: 9680: 9594: 9368: 9338: 9318: 9298: 9260: 9222: 9193: 9173: 9153: 8893: 8851: 8772: 8703: 8665: 8539: 8270: 8243: 8221: 8199: 8168: 8128: 8090: 8061: 7954: 7888: 7785: 7640: 7451: 7417: 7320: 7216: 7139: 7058: 6984: 6955: 6910: 6859: 6779: 6658: 6560: 6445: 6411: 6334: 6250: 6173: 6092: 6030: 5977: 5860: 5711: 5560: 5470: 5381: 5266: 4977: 4851: 4594: 4384: 4325: 4294: 4206: 4138: 4066: 4019: 3846: 3762: 3728: 3588: 3490: 3456: 3355: 3265: 3142: 2992: 2916: 2825: 2789: 2574: 2545: 2452: 2354: 2268: 2173: 2069: 1970: 1889: 1808: 1709: 1607: 1526: 1442: 1398: 1378: 1350: 1322: 1302: 1222: 1165: 1134: 1103: 1046: 1015: 958: 927: 870: 839: 791: 760: 712: 681: 633: 602: 503: 400: 377: 357: 337: 293: 232: 212: 192: 27:
Mathematical model of a system in control engineering
8835:{\displaystyle {\dot {x}}_{2}(t)={\ddot {x}}_{1}(t)} 5702:
which yields the following controllable realization
2526: 11485: 7442:and substituting in the state equation results in 5544:determined by the strictly proper part, and matrix 824:{\displaystyle \mathbf {u} (t)\in \mathbb {R} ^{p}} 745:{\displaystyle \mathbf {y} (t)\in \mathbb {R} ^{q}} 666:{\displaystyle \mathbf {x} (t)\in \mathbb {R} ^{n}} 10896: 10804: 10758: 10476: 10416: 10347: 10290: 10162: 10088: 10068: 10046: 10024: 10002: 9980: 9945: 9817: 9788: 9744: 9665: 9566: 9344: 9324: 9304: 9284: 9246: 9208: 9179: 9159: 9136: 8868: 8834: 8756: 8687: 8645: 8524: 8249: 8227: 8205: 8183: 8152: 8114: 8076: 8041: 7925: 7873: 7761: 7625: 7434: 7400: 7305: 7196: 7124: 7041: 6970: 6925: 6893: 6844: 6770:. This would then result in the simpler equations 6718: 6629: 6545: 6436:and substituting in the state equation results in 6428: 6394: 6319: 6230: 6158: 6067: 5996: 5960: 5843: 5691: 5524: 5453: 5341: 5249: 4950: 4834: 4574: 4337: 4311: 4276: 4186: 4113: 4044: 4002: 3826: 3745: 3711: 3568: 3473: 3439: 3335: 3229: 3092: 2935: 2872: 2808: 2764: 2553: 2513: 2438: 2329: 2254: 2148: 2055: 1950: 1875: 1788: 1695: 1587: 1512: 1404: 1384: 1364: 1336: 1308: 1280: 1206: 1151: 1120: 1087: 1032: 999: 944: 911: 856: 823: 777: 744: 698: 665: 619: 582: 488: 391:state variables is written in the following form: 383: 363: 343: 299: 244: 218: 198: 11018:Analysis and Control of Nonlinear Process Systems 6734:can be made stable through appropriate choice of 785:is called the "input (or control) vector",  12556: 9833:A classic nonlinear system is a simple unforced 7926:{\displaystyle \mathbf {y} (t)=C\mathbf {x} (t)} 6068:{\displaystyle \mathbf {u} (t)=K\mathbf {y} (t)} 11428: 6894:{\displaystyle \mathbf {y} (t)=\mathbf {x} (t)} 226:outputs, we would otherwise have to write down 11238: 10484:is the rotational acceleration of the pendulum 10477:{\displaystyle {\dot {x}}_{2}={\ddot {x}}_{1}} 6726:. This assumes that the closed-loop system is 11646: 11584: 11106: 10054:is coefficient of friction at the pivot point 6024:and setting this as the input to the system: 5551:Here is an example to clear things up a bit: 11660: 11555:Zadeh, Lotfi A.; Desoer, Charles A. (1979). 11388:(6th ed.). John Wiley & Sons, Inc. 6652:appropriately through eigendecomposition of 5359: 4123:multiple-input multiple-output (MIMO) system 4060:is defined as the ratio of output and input 4045:{\displaystyle \mathbf {x} (0)=\mathbf {0} } 11587:Time series analysis by state space methods 11554: 11225:James H. Stock & Mark W. Watson, 1989. 11109:Time series analysis by state space methods 11079:, vol. 2, Elsevier, pp. 415–525, 11074: 11653: 11639: 11174: 10424:is the rotational velocity of the pendulum 10417:{\displaystyle x_{2}(t)={\dot {x}}_{1}(t)} 10163:{\displaystyle {\dot {x}}_{1}(t)=x_{2}(t)} 8757:{\displaystyle x_{2}(t)={\dot {x}}_{1}(t)} 8646:{\displaystyle \mathbf {y} (t)=\left\left} 2809:{\displaystyle s\mathbf {I} -\mathbf {A} } 11535: 11452:(3rd ed.). Oxford University Press. 11260: 11107:Durbin, James; Koopman, Siem Jan (2012). 11059: 4357: 1372:). In the latter case, the time variable 1358: 1330: 864:is the "state (or system) matrix",  811: 732: 653: 80:Learn how and when to remove this message 11429:Antsaklis, P. J.; Michel, A. N. (2007). 11294:State-Space Models with Regime Switching 7936: 6940: 6937:Feedback with setpoint (reference) input 6011: 4054:single-input single-output (SISO) system 322: 43:This article includes a list of general 11589:. Oxford, UK: Oxford University Press. 11139: 9789:{\displaystyle f(\cdot ,\cdot ,\cdot )} 6016:Typical state-space model with feedback 5352:This state-space realization is called 4961:This state-space realization is called 14: 12557: 11504: 11466: 11408: 11323: 11142:IEEE Transactions on Automatic Control 5997:{\displaystyle {\textbf {G}}(\infty )} 11634: 10988:; R. Lakner & M. Gerzson (2001). 9332:are constants, then there is a force 8695:represents the position of the object 8261:The state equation would then become 4368:Any given transfer function which is 2887:) are the system transfer function's 706:is called the "output vector",  12491:Generative adversarial network (GAN) 11447: 11383: 11061:10.17586/2226-1494-2015-15-5-839-848 11042:Vasilyev A.S.; Ushakov A.V. (2015). 9580: 6730:or that the unstable eigenvalues of 3240: 2910:The zeros found in the numerator of 1152:{\displaystyle \mathbf {D} (\cdot )} 1121:{\displaystyle \mathbf {D} (\cdot )} 1033:{\displaystyle \mathbf {C} (\cdot )} 945:{\displaystyle \mathbf {B} (\cdot )} 857:{\displaystyle \mathbf {A} (\cdot )} 778:{\displaystyle \mathbf {u} (\cdot )} 699:{\displaystyle \mathbf {y} (\cdot )} 627:is called the "state vector",  620:{\displaystyle \mathbf {x} (\cdot )} 29: 10348:{\displaystyle x_{1}(t)=\theta (t)} 9828: 8213:is the viscous friction coefficient 6949:In addition to feedback, an input, 6004:constant in the transfer function. 5980: 5944: 5906: 5863: 5827: 5782: 5716: 5563: 5508: 5492: 5473: 5434: 5404: 5384: 5322: 5269: 5233: 5146: 4982: 4387: 2919: 2577: 24: 11420: 6640:The advantage of this is that the 5988: 5500: 5442: 5414: 5411: 5364:Transfer functions which are only 3111:is the number of state variables. 2965: 2883:The roots of this polynomial (the 278: 180:Kronecker vector-matrix structures 49:it lacks sufficient corresponding 25: 12591: 11606: 10032:is the gravitational acceleration 8842:is the acceleration of the object 7776:, which reduces the equations to 4013:Assuming zero initial conditions 2527:Example: continuous-time LTI case 1365:{\displaystyle t\in \mathbb {Z} } 1337:{\displaystyle t\in \mathbb {R} } 318: 178:, which makes it possible to use 12529: 12528: 12508: 11585:Durbin, J.; Koopman, S. (2001). 10604: 10502: 9699: 9682: 9620: 9601: 9598: 8853: 8620: 8616: 8595: 8591: 8541: 8509: 8445: 8420: 8318: 8284: 7910: 7890: 7858: 7838: 7790: 7746: 7694: 7642: 7610: 7536: 7456: 7419: 7411:solving the output equation for 7385: 7365: 7342: 7322: 7290: 7270: 7247: 7221: 7181: 7161: 7141: 7109: 7089: 7063: 7026: 7009: 6986: 6878: 6861: 6829: 6784: 6614: 6562: 6530: 6450: 6413: 6405:solving the output equation for 6379: 6356: 6336: 6304: 6281: 6255: 6215: 6195: 6175: 6143: 6123: 6097: 6052: 6032: 4932: 4853: 4819: 4762: 4599: 4296: 4270: 4262: 4244: 4236: 4225: 4208: 4171: 4157: 4140: 4038: 4021: 3984: 3979: 3959: 3954: 3936: 3928: 3905: 3887: 3879: 3865: 3848: 3808: 3803: 3786: 3781: 3764: 3730: 3693: 3688: 3670: 3662: 3639: 3621: 3613: 3590: 3553: 3548: 3531: 3514: 3506: 3498: 3458: 3421: 3416: 3399: 3394: 3377: 3360: 3320: 3315: 3298: 3293: 3270: 3194: 3188: 3172: 3167: 3158: 3114: 3069: 3052: 3039: 3028: 3020: 3015: 3008: 2936:{\displaystyle {\textbf {G}}(s)} 2858: 2850: 2802: 2794: 2547: 2498: 2493: 2476: 2471: 2454: 2423: 2418: 2401: 2396: 2379: 2359: 2314: 2309: 2292: 2287: 2270: 2239: 2234: 2217: 2212: 2195: 2178: 2133: 2119: 2102: 2088: 2071: 2040: 2026: 2009: 1995: 1972: 1935: 1930: 1913: 1908: 1891: 1860: 1855: 1838: 1833: 1810: 1800:Explicit discrete time-invariant 1773: 1759: 1742: 1728: 1711: 1680: 1666: 1649: 1635: 1612: 1572: 1567: 1550: 1545: 1528: 1497: 1492: 1475: 1470: 1447: 1418: 1265: 1227: 1176: 1136: 1105: 1057: 1017: 969: 929: 881: 841: 793: 762: 714: 683: 635: 604: 567: 553: 536: 522: 505: 473: 459: 442: 428: 405: 34: 11471:(3rd ed.). Prentice Hall. 11450:Linear System Theory and Design 11402: 11377: 11364: 11317: 11285: 11241:Journal of Applied Econometrics 8869:{\displaystyle \mathbf {y} (t)} 7435:{\displaystyle \mathbf {y} (t)} 6429:{\displaystyle \mathbf {y} (t)} 4319:is a matrix with the dimension 4312:{\displaystyle \mathbf {G} (s)} 3746:{\displaystyle \mathbf {X} (s)} 3474:{\displaystyle \mathbf {X} (s)} 12441:Recurrent neural network (RNN) 12431:Differentiable neural computer 11302:10.7551/mitpress/6444.003.0013 11232: 11219: 11168: 11133: 11100: 11068: 11035: 11008: 10978: 10967:for a statistical application. 10742: 10736: 10703: 10697: 10659: 10653: 10629: 10626: 10620: 10608: 10589: 10583: 10557: 10551: 10518: 10512: 10411: 10405: 10380: 10374: 10342: 10336: 10327: 10321: 10285: 10279: 10246: 10240: 10203: 10197: 10157: 10151: 10135: 10129: 9975: 9969: 9940: 9934: 9910: 9904: 9877: 9871: 9812: 9806: 9783: 9765: 9739: 9736: 9730: 9721: 9715: 9703: 9692: 9686: 9660: 9657: 9651: 9642: 9636: 9624: 9613: 9607: 9285:{\displaystyle {\ddot {y}}(t)} 9279: 9273: 9241: 9235: 9203: 9197: 8863: 8857: 8829: 8823: 8798: 8792: 8751: 8745: 8720: 8714: 8682: 8676: 8632: 8626: 8607: 8601: 8551: 8545: 8519: 8513: 8461: 8455: 8436: 8430: 8340: 8334: 8306: 8300: 8178: 8172: 8153:{\displaystyle {\ddot {y}}(t)} 8147: 8141: 8109: 8103: 8071: 8065: 8036: 8030: 8018: 8012: 7991: 7985: 7976: 7970: 7920: 7914: 7900: 7894: 7868: 7862: 7848: 7842: 7806: 7800: 7756: 7750: 7704: 7698: 7652: 7646: 7620: 7614: 7546: 7540: 7472: 7466: 7429: 7423: 7395: 7389: 7375: 7369: 7352: 7346: 7332: 7326: 7300: 7294: 7280: 7274: 7257: 7251: 7237: 7231: 7191: 7185: 7171: 7165: 7151: 7145: 7119: 7113: 7099: 7093: 7079: 7073: 7036: 7030: 7019: 7013: 6996: 6990: 6965: 6959: 6945:Output feedback with set point 6888: 6882: 6871: 6865: 6839: 6833: 6800: 6794: 6624: 6618: 6572: 6566: 6540: 6534: 6466: 6460: 6423: 6417: 6389: 6383: 6366: 6360: 6346: 6340: 6314: 6308: 6291: 6285: 6271: 6265: 6225: 6219: 6205: 6199: 6185: 6179: 6153: 6147: 6133: 6127: 6113: 6107: 6062: 6056: 6042: 6036: 5991: 5985: 5955: 5949: 5917: 5911: 5874: 5868: 5838: 5832: 5793: 5787: 5732: 5726: 5574: 5568: 5519: 5513: 5503: 5497: 5484: 5478: 5445: 5439: 5426: 5420: 5395: 5389: 5333: 5327: 5280: 5274: 5244: 5238: 5157: 5151: 4998: 4992: 4942: 4936: 4863: 4857: 4829: 4823: 4772: 4766: 4615: 4609: 4398: 4392: 4306: 4300: 4249: 4229: 4218: 4212: 4181: 4175: 4167: 4161: 4150: 4144: 4114:{\displaystyle G(s)=Y(s)/U(s)} 4108: 4102: 4091: 4085: 4076: 4070: 4031: 4025: 3994: 3988: 3972: 3969: 3963: 3941: 3921: 3915: 3909: 3892: 3872: 3869: 3858: 3852: 3818: 3812: 3796: 3790: 3774: 3768: 3740: 3734: 3703: 3697: 3675: 3655: 3649: 3643: 3626: 3606: 3600: 3594: 3563: 3557: 3541: 3535: 3524: 3518: 3510: 3491: 3468: 3462: 3431: 3425: 3409: 3403: 3387: 3381: 3370: 3364: 3330: 3324: 3308: 3302: 3286: 3280: 2930: 2924: 2863: 2842: 2835: 2829: 2753: 2734: 2731: 2712: 2709: 2690: 2687: 2668: 2663: 2644: 2641: 2622: 2619: 2600: 2588: 2582: 2508: 2502: 2486: 2480: 2464: 2458: 2433: 2427: 2411: 2405: 2389: 2383: 2369: 2363: 2324: 2318: 2302: 2296: 2280: 2274: 2249: 2243: 2227: 2221: 2205: 2199: 2188: 2182: 2143: 2137: 2129: 2123: 2112: 2106: 2098: 2092: 2081: 2075: 2050: 2044: 2036: 2030: 2019: 2013: 2005: 1999: 1988: 1976: 1962:Explicit discrete time-variant 1945: 1939: 1923: 1917: 1901: 1895: 1870: 1864: 1848: 1842: 1826: 1814: 1783: 1777: 1769: 1763: 1752: 1746: 1738: 1732: 1721: 1715: 1690: 1684: 1676: 1670: 1659: 1653: 1645: 1639: 1628: 1622: 1582: 1576: 1560: 1554: 1538: 1532: 1507: 1501: 1485: 1479: 1463: 1457: 1275: 1269: 1243: 1237: 1207:{\displaystyle \dim=q\times p} 1189: 1186: 1180: 1172: 1146: 1140: 1115: 1109: 1088:{\displaystyle \dim=q\times n} 1070: 1067: 1061: 1053: 1040:is the "output matrix",  1027: 1021: 1000:{\displaystyle \dim=n\times p} 982: 979: 973: 965: 939: 933: 912:{\displaystyle \dim=n\times n} 894: 891: 885: 877: 851: 845: 803: 797: 772: 766: 724: 718: 693: 687: 645: 639: 614: 608: 577: 571: 563: 557: 546: 540: 532: 526: 515: 509: 483: 477: 469: 463: 452: 446: 438: 432: 421: 415: 13: 1: 12486:Variational autoencoder (VAE) 12446:Long short-term memory (LSTM) 11713:Computational learning theory 11085:10.1016/bs.hesmac.2016.04.002 10972: 10100:The state equations are then 9247:{\displaystyle {\dot {y}}(t)} 8876:is the position of the object 8764:is the velocity of the object 8115:{\displaystyle {\dot {y}}(t)} 6746:For a strictly proper system 6648:can be controlled by setting 952:is the "input matrix",  98:configuration space (physics) 12466:Convolutional neural network 11625:nonlinear state-space models 11330:Journal of Basic Engineering 11324:Kalman, R. E. (1960-03-01). 10805:{\displaystyle {\dot {x}}=0} 10355:is the angle of the pendulum 9147:which has full rank for all 5548:determined by the constant. 2554:{\displaystyle \mathbf {A} } 7: 12461:Multilayer perceptron (MLP) 11536:Friedland, Bernard (2005). 11505:Sontag, Eduardo D. (1999). 11409:Brogan, William L. (1974). 11386:Control Systems Engineering 11111:. Oxford University Press. 10914: 6007: 4963:controllable canonical form 1392:is usually used instead of 1159:is the zero matrix),  10: 12596: 12537:Artificial neural networks 12451:Gated recurrent unit (GRU) 11677:Differentiable programming 11514:(2nd ed.). Springer. 11467:Khalil, Hassan K. (2001). 11370:Harvey, Andrew C. (1990). 11189:10.1162/089976603765202622 11077:Handbook of Macroeconomics 9981:{\displaystyle \theta (t)} 6741: 4361: 3118: 2969: 2339: 2158: 1960: 1798: 1597: 1432: 1420: 112:state-space representation 91: 18:State space representation 12504: 12418: 12362: 12291: 12224: 12096: 11996: 11989: 11943: 11907: 11870:Artificial neural network 11850: 11726: 11693:Automatic differentiation 11666: 11621:affine state-space models 11617:linear state-space models 10994:. Springer. p. 254. 8257:is the mass of the object 6978:, can be added such that 5360:Proper transfer functions 5354:observable canonical form 4338:{\displaystyle q\times p} 2777:characteristic polynomial 2165:continuous time-invariant 1434:Continuous time-invariant 245:{\displaystyle q\times p} 130:. Such variables, called 12565:Classical control theory 11698:Neuromorphic engineering 11661:Differentiable computing 11448:Chen, Chi-Tsong (1999). 11384:Nise, Norman S. (2010). 11154:10.1109/tac.1975.1100844 11021:. Springer. p. 25. 8688:{\displaystyle x_{1}(t)} 4348:Rosenbrock system matrix 4127:transfer function matrix 2950:The system may still be 1316:can be continuous (e.g. 12471:Residual neural network 11887:Artificial Intelligence 11431:A Linear Systems Primer 11296:, The MIT Press, 2017, 7943:Newton's laws of motion 3753:in the output equation 2346:discrete time-invariant 1599:Continuous time-variant 122:related by first-order 64:more precise citations. 10898: 10806: 10760: 10478: 10418: 10349: 10292: 10164: 10090: 10070: 10048: 10026: 10004: 9982: 9947: 9819: 9790: 9746: 9667: 9568: 9346: 9326: 9306: 9286: 9248: 9210: 9181: 9161: 9138: 8870: 8836: 8758: 8689: 8647: 8526: 8251: 8235:is the spring constant 8229: 8207: 8185: 8154: 8116: 8078: 8043: 7927: 7875: 7763: 7627: 7436: 7402: 7307: 7198: 7126: 7043: 6972: 6946: 6927: 6895: 6846: 6720: 6631: 6547: 6430: 6396: 6321: 6232: 6160: 6075:. Since the values of 6069: 6017: 5998: 5962: 5845: 5693: 5526: 5455: 5343: 5251: 4952: 4836: 4576: 4358:Canonical realizations 4339: 4313: 4278: 4188: 4115: 4046: 4004: 3828: 3747: 3713: 3570: 3475: 3450:Next, we simplify for 3441: 3337: 3231: 3094: 2937: 2874: 2810: 2766: 2555: 2515: 2440: 2331: 2256: 2150: 2057: 1952: 1877: 1790: 1697: 1589: 1514: 1406: 1386: 1366: 1338: 1310: 1282: 1208: 1153: 1122: 1089: 1034: 1001: 946: 913: 858: 825: 779: 746: 700: 667: 621: 584: 490: 385: 365: 345: 328: 301: 246: 220: 200: 124:differential equations 12570:Mathematical modeling 12426:Neural Turing machine 12014:Human image synthesis 11411:Modern Control Theory 10949:of state-space models 10899: 10807: 10777:of a system are when 10761: 10479: 10419: 10350: 10293: 10165: 10091: 10071: 10069:{\displaystyle \ell } 10049: 10027: 10005: 9983: 9948: 9820: 9791: 9747: 9668: 9569: 9347: 9327: 9307: 9287: 9249: 9211: 9182: 9162: 9139: 8871: 8837: 8759: 8690: 8648: 8527: 8252: 8230: 8208: 8186: 8155: 8117: 8079: 8044: 7937:Moving object example 7928: 7876: 7764: 7628: 7437: 7403: 7308: 7199: 7127: 7044: 6973: 6944: 6928: 6896: 6847: 6721: 6632: 6548: 6431: 6397: 6322: 6233: 6161: 6070: 6015: 5999: 5963: 5846: 5694: 5527: 5456: 5344: 5252: 4953: 4837: 4577: 4364:Realization (systems) 4340: 4314: 4279: 4189: 4116: 4047: 4005: 3829: 3748: 3714: 3571: 3476: 3442: 3338: 3232: 3095: 2938: 2897:asymptotically stable 2875: 2811: 2767: 2556: 2516: 2441: 2332: 2257: 2151: 2058: 1953: 1878: 1791: 1698: 1590: 1515: 1407: 1387: 1367: 1339: 1311: 1283: 1209: 1154: 1123: 1090: 1035: 1002: 947: 914: 859: 826: 780: 747: 701: 668: 622: 585: 491: 386: 366: 346: 326: 302: 247: 221: 201: 108:system identification 12575:Time domain analysis 12517:Computer programming 12496:Graph neural network 12071:Text-to-video models 12049:Text-to-image models 11897:Large language model 11882:Scientific computing 11688:Statistical manifold 11683:Information geometry 11557:Linear System Theory 10819: 10781: 10495: 10430: 10361: 10308: 10175: 10107: 10080: 10060: 10038: 10016: 9994: 9963: 9843: 9818:{\displaystyle u(t)} 9800: 9759: 9678: 9592: 9366: 9336: 9316: 9296: 9258: 9220: 9209:{\displaystyle y(t)} 9191: 9171: 9151: 8891: 8849: 8770: 8701: 8663: 8537: 8268: 8241: 8219: 8197: 8184:{\displaystyle u(t)} 8166: 8126: 8088: 8077:{\displaystyle y(t)} 8059: 7952: 7886: 7783: 7638: 7449: 7415: 7318: 7214: 7137: 7056: 6982: 6971:{\displaystyle r(t)} 6953: 6926:{\displaystyle A+BK} 6908: 6857: 6777: 6656: 6558: 6443: 6409: 6332: 6248: 6171: 6090: 6028: 5975: 5858: 5709: 5558: 5468: 5379: 5264: 4975: 4849: 4592: 4382: 4323: 4292: 4204: 4136: 4064: 4017: 3844: 3760: 3726: 3586: 3488: 3454: 3353: 3263: 3140: 2990: 2914: 2823: 2787: 2779:found by taking the 2572: 2543: 2450: 2352: 2266: 2171: 2067: 1968: 1887: 1806: 1707: 1605: 1524: 1440: 1396: 1376: 1348: 1344:) or discrete (e.g. 1320: 1300: 1220: 1163: 1132: 1101: 1044: 1013: 956: 925: 868: 837: 789: 758: 710: 679: 631: 600: 501: 398: 375: 355: 335: 291: 230: 210: 190: 128:difference equations 11863:In-context learning 11703:Pattern recognition 10922:Control engineering 8191:is an applied force 2952:input–output stable 168:algebraic equations 104:control engineering 94:quantum state space 12580:Time series models 12456:Echo state network 12344:JĂĽrgen Schmidhuber 12039:Facial recognition 12034:Speech recognition 11944:Software libraries 11559:. Krieger Pub Co. 11177:Neural Computation 10894: 10888: 10856: 10802: 10756: 10747: 10594: 10474: 10414: 10345: 10288: 10160: 10086: 10066: 10044: 10022: 10000: 9978: 9943: 9815: 9786: 9742: 9663: 9564: 9558: 9519: 9511: 9455: 9427: 9392: 9342: 9322: 9302: 9282: 9244: 9206: 9177: 9157: 9134: 9128: 9058: 9050: 9017: 8959: 8915: 8866: 8832: 8754: 8685: 8643: 8637: 8575: 8522: 8502: 8466: 8404: 8345: 8247: 8225: 8203: 8181: 8150: 8112: 8074: 8039: 7923: 7871: 7759: 7623: 7432: 7398: 7303: 7194: 7122: 7039: 6968: 6947: 6923: 6891: 6842: 6716: 6627: 6543: 6426: 6392: 6317: 6228: 6156: 6065: 6018: 5994: 5958: 5936: 5898: 5841: 5819: 5774: 5689: 5522: 5451: 5339: 5314: 5247: 5225: 5138: 4948: 4925: 4832: 4812: 4755: 4572: 4335: 4309: 4274: 4184: 4111: 4042: 4000: 3824: 3743: 3709: 3566: 3471: 3437: 3333: 3252:First, taking the 3227: 3212: 3090: 3075: 2933: 2905:Lyapunov stability 2870: 2806: 2762: 2551: 2511: 2436: 2327: 2252: 2146: 2053: 1948: 1873: 1786: 1693: 1585: 1510: 1402: 1382: 1362: 1334: 1306: 1278: 1204: 1149: 1118: 1085: 1030: 997: 942: 909: 854: 821: 775: 742: 696: 663: 617: 580: 486: 381: 361: 341: 329: 297: 253:Laplace transforms 242: 216: 196: 170:may be written in 116:mathematical model 12552: 12551: 12314:Stephen Grossberg 12287: 12286: 11596:978-0-19-852354-3 11566:978-0-88275-809-1 11497:978-3-540-44125-0 11469:Nonlinear Systems 11440:978-0-8176-4460-4 11395:978-0-470-54756-4 11342:10.1115/1.3662552 11311:978-0-262-27711-2 11118:978-0-19-964117-8 11094:978-0-444-59487-7 11028:978-1-85233-600-4 11001:978-1-4020-0134-5 10986:Katalin M. Hangos 10793: 10775:stationary points 10722: 10677: 10574: 10542: 10509: 10465: 10443: 10396: 10265: 10220: 10188: 10120: 10089:{\displaystyle m} 10047:{\displaystyle k} 10025:{\displaystyle g} 10003:{\displaystyle m} 9931: 9868: 9604: 9581:Nonlinear systems 9507: 9492: 9345:{\displaystyle u} 9325:{\displaystyle m} 9305:{\displaystyle b} 9270: 9232: 9180:{\displaystyle m} 9160:{\displaystyle b} 9124: 9102: 9088: 9046: 9013: 8998: 8955: 8814: 8783: 8736: 8498: 8400: 8385: 8325: 8291: 8250:{\displaystyle m} 8228:{\displaystyle k} 8206:{\displaystyle b} 8138: 8100: 8009: 7967: 7797: 7463: 7228: 7070: 6791: 6457: 6262: 6104: 6081:negative feedback 5982: 5946: 5908: 5865: 5829: 5784: 5723: 5718: 5681: 5636: 5565: 5510: 5494: 5475: 5436: 5406: 5386: 5324: 5271: 5235: 5148: 4989: 4984: 4606: 4567: 4389: 4352:transfer function 4058:transfer function 3722:Substituting for 3277: 3254:Laplace transform 3247:transfer function 3241:Transfer function 2921: 2901:marginally stable 2757: 2579: 2563:transfer function 2524: 2523: 1619: 1454: 1428:State-space model 1405:{\displaystyle t} 1385:{\displaystyle k} 1309:{\displaystyle t} 1262: 1234: 412: 384:{\displaystyle n} 364:{\displaystyle q} 344:{\displaystyle p} 300:{\displaystyle n} 219:{\displaystyle q} 199:{\displaystyle p} 90: 89: 82: 16:(Redirected from 12587: 12542:Machine learning 12532: 12531: 12512: 12267:Action selection 12257:Self-driving car 12064:Stable Diffusion 12029:Speech synthesis 11994: 11993: 11858:Machine learning 11734:Gradient descent 11655: 11648: 11641: 11632: 11631: 11613:Wolfram language 11600: 11570: 11551: 11532: 11530: 11528: 11513: 11501: 11482: 11463: 11444: 11415: 11414: 11406: 11400: 11399: 11381: 11375: 11368: 11362: 11361: 11321: 11315: 11314: 11289: 11283: 11282: 11264: 11253:10.1002/jae.2306 11236: 11230: 11223: 11217: 11216: 11172: 11166: 11165: 11137: 11131: 11130: 11104: 11098: 11097: 11072: 11066: 11065: 11063: 11039: 11033: 11032: 11012: 11006: 11005: 10982: 10903: 10901: 10900: 10895: 10893: 10892: 10861: 10860: 10853: 10852: 10839: 10838: 10811: 10809: 10808: 10803: 10795: 10794: 10786: 10765: 10763: 10762: 10757: 10752: 10751: 10735: 10734: 10733: 10723: 10721: 10710: 10696: 10695: 10694: 10678: 10670: 10652: 10651: 10607: 10599: 10598: 10582: 10581: 10576: 10575: 10567: 10550: 10549: 10544: 10543: 10535: 10511: 10510: 10505: 10500: 10483: 10481: 10480: 10475: 10473: 10472: 10467: 10466: 10458: 10451: 10450: 10445: 10444: 10436: 10423: 10421: 10420: 10415: 10404: 10403: 10398: 10397: 10389: 10373: 10372: 10354: 10352: 10351: 10346: 10320: 10319: 10297: 10295: 10294: 10289: 10278: 10277: 10276: 10266: 10264: 10253: 10239: 10238: 10237: 10221: 10213: 10196: 10195: 10190: 10189: 10181: 10169: 10167: 10166: 10161: 10150: 10149: 10128: 10127: 10122: 10121: 10113: 10095: 10093: 10092: 10087: 10075: 10073: 10072: 10067: 10053: 10051: 10050: 10045: 10031: 10029: 10028: 10023: 10009: 10007: 10006: 10001: 9987: 9985: 9984: 9979: 9952: 9950: 9949: 9944: 9933: 9932: 9924: 9870: 9869: 9861: 9858: 9857: 9829:Pendulum example 9824: 9822: 9821: 9816: 9795: 9793: 9792: 9787: 9751: 9749: 9748: 9743: 9702: 9685: 9672: 9670: 9669: 9664: 9623: 9606: 9605: 9597: 9573: 9571: 9570: 9565: 9563: 9562: 9524: 9523: 9516: 9515: 9508: 9500: 9493: 9485: 9460: 9459: 9432: 9431: 9397: 9396: 9351: 9349: 9348: 9343: 9331: 9329: 9328: 9323: 9311: 9309: 9308: 9303: 9291: 9289: 9288: 9283: 9272: 9271: 9263: 9253: 9251: 9250: 9245: 9234: 9233: 9225: 9215: 9213: 9212: 9207: 9186: 9184: 9183: 9178: 9166: 9164: 9163: 9158: 9143: 9141: 9140: 9135: 9133: 9132: 9125: 9123: 9122: 9110: 9103: 9095: 9089: 9081: 9063: 9062: 9055: 9054: 9047: 9039: 9022: 9021: 9014: 9006: 8999: 8991: 8964: 8963: 8956: 8948: 8920: 8919: 8875: 8873: 8872: 8867: 8856: 8841: 8839: 8838: 8833: 8822: 8821: 8816: 8815: 8807: 8791: 8790: 8785: 8784: 8776: 8763: 8761: 8760: 8755: 8744: 8743: 8738: 8737: 8729: 8713: 8712: 8694: 8692: 8691: 8686: 8675: 8674: 8652: 8650: 8649: 8644: 8642: 8638: 8625: 8624: 8623: 8600: 8599: 8598: 8580: 8576: 8544: 8531: 8529: 8528: 8523: 8512: 8507: 8506: 8499: 8491: 8471: 8470: 8454: 8453: 8448: 8429: 8428: 8423: 8409: 8408: 8401: 8393: 8386: 8378: 8350: 8349: 8333: 8332: 8327: 8326: 8321: 8316: 8299: 8298: 8293: 8292: 8287: 8282: 8256: 8254: 8253: 8248: 8234: 8232: 8231: 8226: 8212: 8210: 8209: 8204: 8190: 8188: 8187: 8182: 8159: 8157: 8156: 8151: 8140: 8139: 8131: 8121: 8119: 8118: 8113: 8102: 8101: 8093: 8083: 8081: 8080: 8075: 8048: 8046: 8045: 8040: 8011: 8010: 8002: 7969: 7968: 7960: 7932: 7930: 7929: 7924: 7913: 7893: 7880: 7878: 7877: 7872: 7861: 7841: 7836: 7832: 7799: 7798: 7793: 7788: 7768: 7766: 7765: 7760: 7749: 7741: 7740: 7732: 7728: 7697: 7689: 7688: 7680: 7676: 7645: 7632: 7630: 7629: 7624: 7613: 7608: 7604: 7600: 7599: 7591: 7587: 7539: 7534: 7530: 7526: 7525: 7517: 7513: 7465: 7464: 7459: 7454: 7441: 7439: 7438: 7433: 7422: 7407: 7405: 7404: 7399: 7388: 7368: 7345: 7325: 7312: 7310: 7309: 7304: 7293: 7273: 7250: 7230: 7229: 7224: 7219: 7203: 7201: 7200: 7195: 7184: 7164: 7144: 7131: 7129: 7128: 7123: 7112: 7092: 7072: 7071: 7066: 7061: 7048: 7046: 7045: 7040: 7029: 7012: 6989: 6977: 6975: 6974: 6969: 6932: 6930: 6929: 6924: 6900: 6898: 6897: 6892: 6881: 6864: 6851: 6849: 6848: 6843: 6832: 6827: 6823: 6793: 6792: 6787: 6782: 6725: 6723: 6722: 6717: 6715: 6711: 6707: 6706: 6698: 6694: 6636: 6634: 6633: 6628: 6617: 6609: 6608: 6600: 6596: 6565: 6552: 6550: 6549: 6544: 6533: 6528: 6524: 6520: 6519: 6511: 6507: 6459: 6458: 6453: 6448: 6435: 6433: 6432: 6427: 6416: 6401: 6399: 6398: 6393: 6382: 6359: 6339: 6326: 6324: 6323: 6318: 6307: 6284: 6264: 6263: 6258: 6253: 6237: 6235: 6234: 6229: 6218: 6198: 6178: 6165: 6163: 6162: 6157: 6146: 6126: 6106: 6105: 6100: 6095: 6074: 6072: 6071: 6066: 6055: 6035: 6003: 6001: 6000: 5995: 5984: 5983: 5967: 5965: 5964: 5959: 5948: 5947: 5941: 5940: 5910: 5909: 5903: 5902: 5867: 5866: 5850: 5848: 5847: 5842: 5831: 5830: 5824: 5823: 5786: 5785: 5779: 5778: 5725: 5724: 5719: 5714: 5698: 5696: 5695: 5690: 5682: 5680: 5664: 5663: 5653: 5642: 5637: 5635: 5619: 5618: 5608: 5592: 5591: 5581: 5567: 5566: 5531: 5529: 5528: 5523: 5512: 5511: 5496: 5495: 5477: 5476: 5460: 5458: 5457: 5452: 5438: 5437: 5419: 5418: 5417: 5408: 5407: 5388: 5387: 5348: 5346: 5345: 5340: 5326: 5325: 5319: 5318: 5273: 5272: 5256: 5254: 5253: 5248: 5237: 5236: 5230: 5229: 5222: 5221: 5208: 5207: 5194: 5193: 5180: 5179: 5150: 5149: 5143: 5142: 5135: 5134: 5103: 5102: 5071: 5070: 5039: 5038: 4991: 4990: 4985: 4980: 4957: 4955: 4954: 4949: 4935: 4930: 4929: 4922: 4921: 4910: 4909: 4898: 4897: 4886: 4885: 4856: 4841: 4839: 4838: 4833: 4822: 4817: 4816: 4765: 4760: 4759: 4752: 4751: 4737: 4736: 4722: 4721: 4707: 4706: 4608: 4607: 4602: 4597: 4581: 4579: 4578: 4573: 4568: 4566: 4565: 4564: 4549: 4548: 4536: 4535: 4526: 4525: 4513: 4512: 4503: 4502: 4490: 4489: 4479: 4478: 4477: 4462: 4461: 4449: 4448: 4439: 4438: 4426: 4425: 4416: 4415: 4405: 4391: 4390: 4344: 4342: 4341: 4336: 4318: 4316: 4315: 4310: 4299: 4283: 4281: 4280: 4275: 4273: 4265: 4260: 4259: 4247: 4239: 4228: 4211: 4193: 4191: 4190: 4185: 4174: 4160: 4143: 4129:is derived from 4120: 4118: 4117: 4112: 4098: 4051: 4049: 4048: 4043: 4041: 4024: 4009: 4007: 4006: 4001: 3987: 3982: 3962: 3957: 3952: 3951: 3939: 3931: 3908: 3903: 3902: 3890: 3882: 3868: 3851: 3833: 3831: 3830: 3825: 3811: 3806: 3789: 3784: 3767: 3752: 3750: 3749: 3744: 3733: 3718: 3716: 3715: 3710: 3696: 3691: 3686: 3685: 3673: 3665: 3642: 3637: 3636: 3624: 3616: 3593: 3575: 3573: 3572: 3567: 3556: 3551: 3534: 3517: 3509: 3501: 3480: 3478: 3477: 3472: 3461: 3446: 3444: 3443: 3438: 3424: 3419: 3402: 3397: 3380: 3363: 3342: 3340: 3339: 3334: 3323: 3318: 3301: 3296: 3279: 3278: 3273: 3268: 3236: 3234: 3233: 3228: 3217: 3216: 3209: 3208: 3197: 3191: 3175: 3170: 3161: 3099: 3097: 3096: 3091: 3080: 3079: 3072: 3067: 3066: 3055: 3042: 3037: 3036: 3031: 3023: 3018: 3011: 2942: 2940: 2939: 2934: 2923: 2922: 2879: 2877: 2876: 2871: 2866: 2861: 2853: 2845: 2815: 2813: 2812: 2807: 2805: 2797: 2771: 2769: 2768: 2763: 2758: 2756: 2752: 2751: 2730: 2729: 2708: 2707: 2686: 2685: 2666: 2662: 2661: 2640: 2639: 2618: 2617: 2598: 2581: 2580: 2560: 2558: 2557: 2552: 2550: 2520: 2518: 2517: 2512: 2501: 2496: 2479: 2474: 2457: 2445: 2443: 2442: 2437: 2426: 2421: 2404: 2399: 2382: 2362: 2336: 2334: 2333: 2328: 2317: 2312: 2295: 2290: 2273: 2261: 2259: 2258: 2253: 2242: 2237: 2220: 2215: 2198: 2181: 2155: 2153: 2152: 2147: 2136: 2122: 2105: 2091: 2074: 2062: 2060: 2059: 2054: 2043: 2029: 2012: 1998: 1975: 1957: 1955: 1954: 1949: 1938: 1933: 1916: 1911: 1894: 1882: 1880: 1879: 1874: 1863: 1858: 1841: 1836: 1813: 1795: 1793: 1792: 1787: 1776: 1762: 1745: 1731: 1714: 1702: 1700: 1699: 1694: 1683: 1669: 1652: 1638: 1621: 1620: 1615: 1610: 1594: 1592: 1591: 1586: 1575: 1570: 1553: 1548: 1531: 1519: 1517: 1516: 1511: 1500: 1495: 1478: 1473: 1456: 1455: 1450: 1445: 1419: 1411: 1409: 1408: 1403: 1391: 1389: 1388: 1383: 1371: 1369: 1368: 1363: 1361: 1343: 1341: 1340: 1335: 1333: 1315: 1313: 1312: 1307: 1287: 1285: 1284: 1279: 1268: 1263: 1261: 1250: 1236: 1235: 1230: 1225: 1213: 1211: 1210: 1205: 1179: 1158: 1156: 1155: 1150: 1139: 1127: 1125: 1124: 1119: 1108: 1094: 1092: 1091: 1086: 1060: 1039: 1037: 1036: 1031: 1020: 1006: 1004: 1003: 998: 972: 951: 949: 948: 943: 932: 918: 916: 915: 910: 884: 863: 861: 860: 855: 844: 830: 828: 827: 822: 820: 819: 814: 796: 784: 782: 781: 776: 765: 751: 749: 748: 743: 741: 740: 735: 717: 705: 703: 702: 697: 686: 672: 670: 669: 664: 662: 661: 656: 638: 626: 624: 623: 618: 607: 589: 587: 586: 581: 570: 556: 539: 525: 508: 495: 493: 492: 487: 476: 462: 445: 431: 414: 413: 408: 403: 390: 388: 387: 382: 370: 368: 367: 362: 350: 348: 347: 342: 306: 304: 303: 298: 257:frequency domain 251: 249: 248: 243: 225: 223: 222: 217: 205: 203: 202: 197: 164:dynamical system 85: 78: 74: 71: 65: 60:this article by 51:inline citations 38: 37: 30: 21: 12595: 12594: 12590: 12589: 12588: 12586: 12585: 12584: 12555: 12554: 12553: 12548: 12500: 12414: 12380:Google DeepMind 12358: 12324:Geoffrey Hinton 12283: 12220: 12146:Project Debater 12092: 11990:Implementations 11985: 11939: 11903: 11846: 11788:Backpropagation 11722: 11708:Tensor calculus 11662: 11659: 11609: 11604: 11603: 11597: 11573: 11567: 11548: 11526: 11524: 11522: 11511: 11498: 11479: 11460: 11441: 11423: 11421:Further reading 11418: 11407: 11403: 11396: 11382: 11378: 11369: 11365: 11322: 11318: 11312: 11291: 11290: 11286: 11237: 11233: 11224: 11220: 11173: 11169: 11138: 11134: 11119: 11105: 11101: 11095: 11073: 11069: 11040: 11036: 11029: 11013: 11009: 11002: 10983: 10979: 10975: 10970: 10942:Controllability 10917: 10887: 10886: 10880: 10879: 10866: 10865: 10855: 10854: 10848: 10844: 10841: 10840: 10834: 10830: 10823: 10822: 10820: 10817: 10816: 10785: 10784: 10782: 10779: 10778: 10746: 10745: 10729: 10725: 10724: 10714: 10709: 10690: 10686: 10685: 10669: 10663: 10662: 10647: 10643: 10636: 10635: 10603: 10593: 10592: 10577: 10566: 10565: 10564: 10561: 10560: 10545: 10534: 10533: 10532: 10525: 10524: 10501: 10499: 10498: 10496: 10493: 10492: 10468: 10457: 10456: 10455: 10446: 10435: 10434: 10433: 10431: 10428: 10427: 10399: 10388: 10387: 10386: 10368: 10364: 10362: 10359: 10358: 10315: 10311: 10309: 10306: 10305: 10272: 10268: 10267: 10257: 10252: 10233: 10229: 10228: 10212: 10191: 10180: 10179: 10178: 10176: 10173: 10172: 10145: 10141: 10123: 10112: 10111: 10110: 10108: 10105: 10104: 10081: 10078: 10077: 10061: 10058: 10057: 10039: 10036: 10035: 10017: 10014: 10013: 9995: 9992: 9991: 9964: 9961: 9960: 9923: 9922: 9860: 9859: 9853: 9849: 9844: 9841: 9840: 9831: 9801: 9798: 9797: 9760: 9757: 9756: 9698: 9681: 9679: 9676: 9675: 9619: 9596: 9595: 9593: 9590: 9589: 9583: 9557: 9556: 9551: 9545: 9544: 9539: 9529: 9528: 9518: 9517: 9510: 9509: 9499: 9494: 9484: 9478: 9477: 9472: 9462: 9461: 9454: 9453: 9448: 9438: 9437: 9434: 9433: 9426: 9425: 9420: 9410: 9409: 9402: 9401: 9391: 9390: 9381: 9380: 9370: 9369: 9367: 9364: 9363: 9337: 9334: 9333: 9317: 9314: 9313: 9297: 9294: 9293: 9262: 9261: 9259: 9256: 9255: 9224: 9223: 9221: 9218: 9217: 9192: 9189: 9188: 9172: 9169: 9168: 9152: 9149: 9148: 9127: 9126: 9118: 9114: 9109: 9104: 9094: 9091: 9090: 9080: 9078: 9068: 9067: 9057: 9056: 9049: 9048: 9038: 9035: 9034: 9024: 9023: 9016: 9015: 9005: 9000: 8990: 8984: 8983: 8978: 8968: 8967: 8965: 8958: 8957: 8947: 8944: 8943: 8933: 8932: 8925: 8924: 8914: 8913: 8905: 8895: 8894: 8892: 8889: 8888: 8882:controllability 8852: 8850: 8847: 8846: 8817: 8806: 8805: 8804: 8786: 8775: 8774: 8773: 8771: 8768: 8767: 8739: 8728: 8727: 8726: 8708: 8704: 8702: 8699: 8698: 8670: 8666: 8664: 8661: 8660: 8636: 8635: 8619: 8615: 8614: 8611: 8610: 8594: 8590: 8589: 8585: 8581: 8574: 8573: 8568: 8561: 8557: 8540: 8538: 8535: 8534: 8508: 8501: 8500: 8490: 8487: 8486: 8476: 8475: 8465: 8464: 8449: 8444: 8443: 8440: 8439: 8424: 8419: 8418: 8411: 8410: 8403: 8402: 8392: 8387: 8377: 8371: 8370: 8365: 8355: 8354: 8344: 8343: 8328: 8317: 8315: 8314: 8313: 8310: 8309: 8294: 8283: 8281: 8280: 8279: 8272: 8271: 8269: 8266: 8265: 8242: 8239: 8238: 8220: 8217: 8216: 8198: 8195: 8194: 8167: 8164: 8163: 8160:is acceleration 8130: 8129: 8127: 8124: 8123: 8092: 8091: 8089: 8086: 8085: 8060: 8057: 8056: 8001: 8000: 7959: 7958: 7953: 7950: 7949: 7939: 7909: 7889: 7887: 7884: 7883: 7857: 7837: 7816: 7812: 7789: 7787: 7786: 7784: 7781: 7780: 7745: 7733: 7715: 7711: 7710: 7693: 7681: 7663: 7659: 7658: 7641: 7639: 7636: 7635: 7609: 7592: 7574: 7570: 7569: 7559: 7555: 7535: 7518: 7500: 7496: 7495: 7482: 7478: 7455: 7453: 7452: 7450: 7447: 7446: 7418: 7416: 7413: 7412: 7384: 7364: 7341: 7321: 7319: 7316: 7315: 7289: 7269: 7246: 7220: 7218: 7217: 7215: 7212: 7211: 7180: 7160: 7140: 7138: 7135: 7134: 7108: 7088: 7062: 7060: 7059: 7057: 7054: 7053: 7025: 7008: 6985: 6983: 6980: 6979: 6954: 6951: 6950: 6939: 6909: 6906: 6905: 6877: 6860: 6858: 6855: 6854: 6828: 6810: 6806: 6783: 6781: 6780: 6778: 6775: 6774: 6768:Identity matrix 6758:, which yields 6744: 6699: 6681: 6677: 6676: 6663: 6659: 6657: 6654: 6653: 6613: 6601: 6583: 6579: 6578: 6561: 6559: 6556: 6555: 6529: 6512: 6494: 6490: 6489: 6476: 6472: 6449: 6447: 6446: 6444: 6441: 6440: 6412: 6410: 6407: 6406: 6378: 6355: 6335: 6333: 6330: 6329: 6303: 6280: 6254: 6252: 6251: 6249: 6246: 6245: 6214: 6194: 6174: 6172: 6169: 6168: 6142: 6122: 6096: 6094: 6093: 6091: 6088: 6087: 6051: 6031: 6029: 6026: 6025: 6010: 5979: 5978: 5976: 5973: 5972: 5943: 5942: 5935: 5934: 5924: 5923: 5905: 5904: 5897: 5896: 5891: 5881: 5880: 5862: 5861: 5859: 5856: 5855: 5826: 5825: 5818: 5817: 5811: 5810: 5800: 5799: 5781: 5780: 5773: 5772: 5767: 5761: 5760: 5752: 5739: 5738: 5715: 5713: 5712: 5710: 5707: 5706: 5659: 5655: 5654: 5643: 5641: 5614: 5610: 5609: 5587: 5583: 5582: 5580: 5562: 5561: 5559: 5556: 5555: 5507: 5506: 5491: 5490: 5472: 5471: 5469: 5466: 5465: 5433: 5432: 5410: 5409: 5403: 5402: 5401: 5383: 5382: 5380: 5377: 5376: 5370:strictly proper 5362: 5321: 5320: 5313: 5312: 5307: 5302: 5297: 5287: 5286: 5268: 5267: 5265: 5262: 5261: 5232: 5231: 5224: 5223: 5217: 5213: 5210: 5209: 5203: 5199: 5196: 5195: 5189: 5185: 5182: 5181: 5175: 5171: 5164: 5163: 5145: 5144: 5137: 5136: 5130: 5126: 5121: 5116: 5111: 5105: 5104: 5098: 5094: 5089: 5084: 5079: 5073: 5072: 5066: 5062: 5057: 5052: 5047: 5041: 5040: 5034: 5030: 5025: 5020: 5015: 5005: 5004: 4981: 4979: 4978: 4976: 4973: 4972: 4931: 4924: 4923: 4917: 4913: 4911: 4905: 4901: 4899: 4893: 4889: 4887: 4881: 4877: 4870: 4869: 4852: 4850: 4847: 4846: 4818: 4811: 4810: 4804: 4803: 4797: 4796: 4790: 4789: 4779: 4778: 4761: 4754: 4753: 4747: 4743: 4738: 4732: 4728: 4723: 4717: 4713: 4708: 4702: 4698: 4692: 4691: 4686: 4681: 4676: 4670: 4669: 4664: 4659: 4654: 4648: 4647: 4642: 4637: 4632: 4622: 4621: 4598: 4596: 4595: 4593: 4590: 4589: 4560: 4556: 4544: 4540: 4531: 4527: 4521: 4517: 4508: 4504: 4498: 4494: 4485: 4481: 4480: 4473: 4469: 4457: 4453: 4444: 4440: 4434: 4430: 4421: 4417: 4411: 4407: 4406: 4404: 4386: 4385: 4383: 4380: 4379: 4370:strictly proper 4366: 4360: 4324: 4321: 4320: 4295: 4293: 4290: 4289: 4269: 4261: 4252: 4248: 4243: 4235: 4224: 4207: 4205: 4202: 4201: 4170: 4156: 4139: 4137: 4134: 4133: 4094: 4065: 4062: 4061: 4037: 4020: 4018: 4015: 4014: 3983: 3978: 3958: 3953: 3944: 3940: 3935: 3927: 3904: 3895: 3891: 3886: 3878: 3864: 3847: 3845: 3842: 3841: 3807: 3802: 3785: 3780: 3763: 3761: 3758: 3757: 3729: 3727: 3724: 3723: 3692: 3687: 3678: 3674: 3669: 3661: 3638: 3629: 3625: 3620: 3612: 3589: 3587: 3584: 3583: 3552: 3547: 3530: 3513: 3505: 3497: 3489: 3486: 3485: 3457: 3455: 3452: 3451: 3420: 3415: 3398: 3393: 3376: 3359: 3354: 3351: 3350: 3319: 3314: 3297: 3292: 3269: 3267: 3266: 3264: 3261: 3260: 3243: 3211: 3210: 3198: 3193: 3192: 3187: 3184: 3183: 3177: 3176: 3171: 3166: 3163: 3162: 3157: 3150: 3149: 3141: 3138: 3137: 3133:if and only if 3123: 3117: 3074: 3073: 3068: 3056: 3051: 3050: 3048: 3043: 3038: 3032: 3027: 3026: 3024: 3019: 3014: 3012: 3007: 3000: 2999: 2991: 2988: 2987: 2974: 2972:Controllability 2968: 2966:Controllability 2918: 2917: 2915: 2912: 2911: 2862: 2857: 2849: 2841: 2824: 2821: 2820: 2801: 2793: 2788: 2785: 2784: 2747: 2743: 2725: 2721: 2703: 2699: 2681: 2677: 2667: 2657: 2653: 2635: 2631: 2613: 2609: 2599: 2597: 2576: 2575: 2573: 2570: 2569: 2546: 2544: 2541: 2540: 2529: 2497: 2492: 2475: 2470: 2453: 2451: 2448: 2447: 2446: 2422: 2417: 2400: 2395: 2378: 2358: 2353: 2350: 2349: 2345: 2313: 2308: 2291: 2286: 2269: 2267: 2264: 2263: 2262: 2238: 2233: 2216: 2211: 2194: 2177: 2172: 2169: 2168: 2164: 2132: 2118: 2101: 2087: 2070: 2068: 2065: 2064: 2063: 2039: 2025: 2008: 1994: 1971: 1969: 1966: 1965: 1934: 1929: 1912: 1907: 1890: 1888: 1885: 1884: 1883: 1859: 1854: 1837: 1832: 1809: 1807: 1804: 1803: 1772: 1758: 1741: 1727: 1710: 1708: 1705: 1704: 1703: 1679: 1665: 1648: 1634: 1611: 1609: 1608: 1606: 1603: 1602: 1571: 1566: 1549: 1544: 1527: 1525: 1522: 1521: 1520: 1496: 1491: 1474: 1469: 1446: 1444: 1443: 1441: 1438: 1437: 1397: 1394: 1393: 1377: 1374: 1373: 1357: 1349: 1346: 1345: 1329: 1321: 1318: 1317: 1301: 1298: 1297: 1264: 1254: 1249: 1226: 1224: 1223: 1221: 1218: 1217: 1175: 1164: 1161: 1160: 1135: 1133: 1130: 1129: 1104: 1102: 1099: 1098: 1056: 1045: 1042: 1041: 1016: 1014: 1011: 1010: 968: 957: 954: 953: 928: 926: 923: 922: 880: 869: 866: 865: 840: 838: 835: 834: 815: 810: 809: 792: 790: 787: 786: 761: 759: 756: 755: 736: 731: 730: 713: 711: 708: 707: 682: 680: 677: 676: 657: 652: 651: 634: 632: 629: 628: 603: 601: 598: 597: 566: 552: 535: 521: 504: 502: 499: 498: 472: 458: 441: 427: 404: 402: 401: 399: 396: 395: 376: 373: 372: 356: 353: 352: 336: 333: 332: 321: 292: 289: 288: 285:state variables 281: 279:State variables 231: 228: 227: 211: 208: 207: 191: 188: 187: 149:geometric space 132:state variables 100: 86: 75: 69: 66: 56:Please help to 55: 39: 35: 28: 23: 22: 15: 12: 11: 5: 12593: 12583: 12582: 12577: 12572: 12567: 12550: 12549: 12547: 12546: 12545: 12544: 12539: 12526: 12525: 12524: 12519: 12505: 12502: 12501: 12499: 12498: 12493: 12488: 12483: 12478: 12473: 12468: 12463: 12458: 12453: 12448: 12443: 12438: 12433: 12428: 12422: 12420: 12416: 12415: 12413: 12412: 12407: 12402: 12397: 12392: 12387: 12382: 12377: 12372: 12366: 12364: 12360: 12359: 12357: 12356: 12354:Ilya Sutskever 12351: 12346: 12341: 12336: 12331: 12326: 12321: 12319:Demis Hassabis 12316: 12311: 12309:Ian Goodfellow 12306: 12301: 12295: 12293: 12289: 12288: 12285: 12284: 12282: 12281: 12276: 12275: 12274: 12264: 12259: 12254: 12249: 12244: 12239: 12234: 12228: 12226: 12222: 12221: 12219: 12218: 12213: 12208: 12203: 12198: 12193: 12188: 12183: 12178: 12173: 12168: 12163: 12158: 12153: 12148: 12143: 12138: 12137: 12136: 12126: 12121: 12116: 12111: 12106: 12100: 12098: 12094: 12093: 12091: 12090: 12085: 12084: 12083: 12078: 12068: 12067: 12066: 12061: 12056: 12046: 12041: 12036: 12031: 12026: 12021: 12016: 12011: 12006: 12000: 11998: 11991: 11987: 11986: 11984: 11983: 11978: 11973: 11968: 11963: 11958: 11953: 11947: 11945: 11941: 11940: 11938: 11937: 11932: 11927: 11922: 11917: 11911: 11909: 11905: 11904: 11902: 11901: 11900: 11899: 11892:Language model 11889: 11884: 11879: 11878: 11877: 11867: 11866: 11865: 11854: 11852: 11848: 11847: 11845: 11844: 11842:Autoregression 11839: 11834: 11833: 11832: 11822: 11820:Regularization 11817: 11816: 11815: 11810: 11805: 11795: 11790: 11785: 11783:Loss functions 11780: 11775: 11770: 11765: 11760: 11759: 11758: 11748: 11743: 11742: 11741: 11730: 11728: 11724: 11723: 11721: 11720: 11718:Inductive bias 11715: 11710: 11705: 11700: 11695: 11690: 11685: 11680: 11672: 11670: 11664: 11663: 11658: 11657: 11650: 11643: 11635: 11629: 11628: 11615:functions for 11608: 11607:External links 11605: 11602: 11601: 11595: 11581: 11580: 11579: 11577: 11572: 11571: 11565: 11552: 11546: 11533: 11520: 11502: 11496: 11483: 11477: 11464: 11458: 11445: 11439: 11433:. Birkhauser. 11425: 11424: 11422: 11419: 11417: 11416: 11401: 11394: 11376: 11363: 11316: 11310: 11284: 11247:(1): 133–160. 11231: 11218: 11183:(5): 965–991. 11167: 11132: 11117: 11099: 11093: 11067: 11054:(5): 839–848. 11034: 11027: 11007: 11000: 10976: 10974: 10971: 10969: 10968: 10962: 10956: 10950: 10947:Discretization 10944: 10939: 10934: 10932:State observer 10929: 10927:Control theory 10924: 10918: 10916: 10913: 10905: 10904: 10891: 10885: 10882: 10881: 10878: 10875: 10872: 10871: 10869: 10864: 10859: 10851: 10847: 10843: 10842: 10837: 10833: 10829: 10828: 10826: 10801: 10798: 10792: 10789: 10767: 10766: 10755: 10750: 10744: 10741: 10738: 10732: 10728: 10720: 10717: 10713: 10708: 10705: 10702: 10699: 10693: 10689: 10684: 10681: 10676: 10673: 10668: 10665: 10664: 10661: 10658: 10655: 10650: 10646: 10642: 10641: 10639: 10634: 10631: 10628: 10625: 10622: 10619: 10616: 10613: 10610: 10606: 10602: 10597: 10591: 10588: 10585: 10580: 10573: 10570: 10563: 10562: 10559: 10556: 10553: 10548: 10541: 10538: 10531: 10530: 10528: 10523: 10520: 10517: 10514: 10508: 10504: 10486: 10485: 10471: 10464: 10461: 10454: 10449: 10442: 10439: 10425: 10413: 10410: 10407: 10402: 10395: 10392: 10385: 10382: 10379: 10376: 10371: 10367: 10356: 10344: 10341: 10338: 10335: 10332: 10329: 10326: 10323: 10318: 10314: 10299: 10298: 10287: 10284: 10281: 10275: 10271: 10263: 10260: 10256: 10251: 10248: 10245: 10242: 10236: 10232: 10227: 10224: 10219: 10216: 10211: 10208: 10205: 10202: 10199: 10194: 10187: 10184: 10170: 10159: 10156: 10153: 10148: 10144: 10140: 10137: 10134: 10131: 10126: 10119: 10116: 10098: 10097: 10085: 10065: 10055: 10043: 10033: 10021: 10011: 9999: 9989: 9977: 9974: 9971: 9968: 9954: 9953: 9942: 9939: 9936: 9930: 9927: 9921: 9918: 9915: 9912: 9909: 9906: 9903: 9900: 9897: 9894: 9891: 9888: 9885: 9882: 9879: 9876: 9873: 9867: 9864: 9856: 9852: 9848: 9830: 9827: 9814: 9811: 9808: 9805: 9785: 9782: 9779: 9776: 9773: 9770: 9767: 9764: 9753: 9752: 9741: 9738: 9735: 9732: 9729: 9726: 9723: 9720: 9717: 9714: 9711: 9708: 9705: 9701: 9697: 9694: 9691: 9688: 9684: 9673: 9662: 9659: 9656: 9653: 9650: 9647: 9644: 9641: 9638: 9635: 9632: 9629: 9626: 9622: 9618: 9615: 9612: 9609: 9603: 9600: 9582: 9579: 9575: 9574: 9561: 9555: 9552: 9550: 9547: 9546: 9543: 9540: 9538: 9535: 9534: 9532: 9527: 9522: 9514: 9506: 9503: 9498: 9495: 9491: 9488: 9483: 9480: 9479: 9476: 9473: 9471: 9468: 9467: 9465: 9458: 9452: 9449: 9447: 9444: 9443: 9441: 9436: 9435: 9430: 9424: 9421: 9419: 9416: 9415: 9413: 9408: 9407: 9405: 9400: 9395: 9389: 9386: 9383: 9382: 9379: 9376: 9375: 9373: 9341: 9321: 9301: 9292:), and if the 9281: 9278: 9275: 9269: 9266: 9243: 9240: 9237: 9231: 9228: 9205: 9202: 9199: 9196: 9176: 9156: 9145: 9144: 9131: 9121: 9117: 9113: 9108: 9105: 9101: 9098: 9093: 9092: 9087: 9084: 9079: 9077: 9074: 9073: 9071: 9066: 9061: 9053: 9045: 9042: 9037: 9036: 9033: 9030: 9029: 9027: 9020: 9012: 9009: 9004: 9001: 8997: 8994: 8989: 8986: 8985: 8982: 8979: 8977: 8974: 8973: 8971: 8966: 8962: 8954: 8951: 8946: 8945: 8942: 8939: 8938: 8936: 8931: 8930: 8928: 8923: 8918: 8912: 8909: 8906: 8904: 8901: 8900: 8898: 8878: 8877: 8865: 8862: 8859: 8855: 8843: 8831: 8828: 8825: 8820: 8813: 8810: 8803: 8800: 8797: 8794: 8789: 8782: 8779: 8765: 8753: 8750: 8747: 8742: 8735: 8732: 8725: 8722: 8719: 8716: 8711: 8707: 8696: 8684: 8681: 8678: 8673: 8669: 8654: 8653: 8641: 8634: 8631: 8628: 8622: 8618: 8613: 8612: 8609: 8606: 8603: 8597: 8593: 8588: 8587: 8584: 8579: 8572: 8569: 8567: 8564: 8563: 8560: 8556: 8553: 8550: 8547: 8543: 8532: 8521: 8518: 8515: 8511: 8505: 8497: 8494: 8489: 8488: 8485: 8482: 8481: 8479: 8474: 8469: 8463: 8460: 8457: 8452: 8447: 8442: 8441: 8438: 8435: 8432: 8427: 8422: 8417: 8416: 8414: 8407: 8399: 8396: 8391: 8388: 8384: 8381: 8376: 8373: 8372: 8369: 8366: 8364: 8361: 8360: 8358: 8353: 8348: 8342: 8339: 8336: 8331: 8324: 8320: 8312: 8311: 8308: 8305: 8302: 8297: 8290: 8286: 8278: 8277: 8275: 8259: 8258: 8246: 8236: 8224: 8214: 8202: 8192: 8180: 8177: 8174: 8171: 8161: 8149: 8146: 8143: 8137: 8134: 8111: 8108: 8105: 8099: 8096: 8073: 8070: 8067: 8064: 8050: 8049: 8038: 8035: 8032: 8029: 8026: 8023: 8020: 8017: 8014: 8008: 8005: 7999: 7996: 7993: 7990: 7987: 7984: 7981: 7978: 7975: 7972: 7966: 7963: 7957: 7938: 7935: 7934: 7933: 7922: 7919: 7916: 7912: 7908: 7905: 7902: 7899: 7896: 7892: 7881: 7870: 7867: 7864: 7860: 7856: 7853: 7850: 7847: 7844: 7840: 7835: 7831: 7828: 7825: 7822: 7819: 7815: 7811: 7808: 7805: 7802: 7796: 7792: 7770: 7769: 7758: 7755: 7752: 7748: 7744: 7739: 7736: 7731: 7727: 7724: 7721: 7718: 7714: 7709: 7706: 7703: 7700: 7696: 7692: 7687: 7684: 7679: 7675: 7672: 7669: 7666: 7662: 7657: 7654: 7651: 7648: 7644: 7633: 7622: 7619: 7616: 7612: 7607: 7603: 7598: 7595: 7590: 7586: 7583: 7580: 7577: 7573: 7568: 7565: 7562: 7558: 7554: 7551: 7548: 7545: 7542: 7538: 7533: 7529: 7524: 7521: 7516: 7512: 7509: 7506: 7503: 7499: 7494: 7491: 7488: 7485: 7481: 7477: 7474: 7471: 7468: 7462: 7458: 7431: 7428: 7425: 7421: 7409: 7408: 7397: 7394: 7391: 7387: 7383: 7380: 7377: 7374: 7371: 7367: 7363: 7360: 7357: 7354: 7351: 7348: 7344: 7340: 7337: 7334: 7331: 7328: 7324: 7313: 7302: 7299: 7296: 7292: 7288: 7285: 7282: 7279: 7276: 7272: 7268: 7265: 7262: 7259: 7256: 7253: 7249: 7245: 7242: 7239: 7236: 7233: 7227: 7223: 7205: 7204: 7193: 7190: 7187: 7183: 7179: 7176: 7173: 7170: 7167: 7163: 7159: 7156: 7153: 7150: 7147: 7143: 7132: 7121: 7118: 7115: 7111: 7107: 7104: 7101: 7098: 7095: 7091: 7087: 7084: 7081: 7078: 7075: 7069: 7065: 7038: 7035: 7032: 7028: 7024: 7021: 7018: 7015: 7011: 7007: 7004: 7001: 6998: 6995: 6992: 6988: 6967: 6964: 6961: 6958: 6938: 6935: 6922: 6919: 6916: 6913: 6902: 6901: 6890: 6887: 6884: 6880: 6876: 6873: 6870: 6867: 6863: 6852: 6841: 6838: 6835: 6831: 6826: 6822: 6819: 6816: 6813: 6809: 6805: 6802: 6799: 6796: 6790: 6786: 6743: 6740: 6714: 6710: 6705: 6702: 6697: 6693: 6690: 6687: 6684: 6680: 6675: 6672: 6669: 6666: 6662: 6638: 6637: 6626: 6623: 6620: 6616: 6612: 6607: 6604: 6599: 6595: 6592: 6589: 6586: 6582: 6577: 6574: 6571: 6568: 6564: 6553: 6542: 6539: 6536: 6532: 6527: 6523: 6518: 6515: 6510: 6506: 6503: 6500: 6497: 6493: 6488: 6485: 6482: 6479: 6475: 6471: 6468: 6465: 6462: 6456: 6452: 6425: 6422: 6419: 6415: 6403: 6402: 6391: 6388: 6385: 6381: 6377: 6374: 6371: 6368: 6365: 6362: 6358: 6354: 6351: 6348: 6345: 6342: 6338: 6327: 6316: 6313: 6310: 6306: 6302: 6299: 6296: 6293: 6290: 6287: 6283: 6279: 6276: 6273: 6270: 6267: 6261: 6257: 6239: 6238: 6227: 6224: 6221: 6217: 6213: 6210: 6207: 6204: 6201: 6197: 6193: 6190: 6187: 6184: 6181: 6177: 6166: 6155: 6152: 6149: 6145: 6141: 6138: 6135: 6132: 6129: 6125: 6121: 6118: 6115: 6112: 6109: 6103: 6099: 6064: 6061: 6058: 6054: 6050: 6047: 6044: 6041: 6038: 6034: 6009: 6006: 5993: 5990: 5987: 5969: 5968: 5957: 5954: 5951: 5939: 5933: 5930: 5929: 5927: 5922: 5919: 5916: 5913: 5901: 5895: 5892: 5890: 5887: 5886: 5884: 5879: 5876: 5873: 5870: 5852: 5851: 5840: 5837: 5834: 5822: 5816: 5813: 5812: 5809: 5806: 5805: 5803: 5798: 5795: 5792: 5789: 5777: 5771: 5768: 5766: 5763: 5762: 5759: 5756: 5753: 5751: 5748: 5745: 5744: 5742: 5737: 5734: 5731: 5728: 5722: 5700: 5699: 5688: 5685: 5679: 5676: 5673: 5670: 5667: 5662: 5658: 5652: 5649: 5646: 5640: 5634: 5631: 5628: 5625: 5622: 5617: 5613: 5607: 5604: 5601: 5598: 5595: 5590: 5586: 5579: 5576: 5573: 5570: 5521: 5518: 5515: 5505: 5502: 5499: 5489: 5486: 5483: 5480: 5462: 5461: 5450: 5447: 5444: 5441: 5431: 5428: 5425: 5422: 5416: 5413: 5400: 5397: 5394: 5391: 5361: 5358: 5350: 5349: 5338: 5335: 5332: 5329: 5317: 5311: 5308: 5306: 5303: 5301: 5298: 5296: 5293: 5292: 5290: 5285: 5282: 5279: 5276: 5258: 5257: 5246: 5243: 5240: 5228: 5220: 5216: 5212: 5211: 5206: 5202: 5198: 5197: 5192: 5188: 5184: 5183: 5178: 5174: 5170: 5169: 5167: 5162: 5159: 5156: 5153: 5141: 5133: 5129: 5125: 5122: 5120: 5117: 5115: 5112: 5110: 5107: 5106: 5101: 5097: 5093: 5090: 5088: 5085: 5083: 5080: 5078: 5075: 5074: 5069: 5065: 5061: 5058: 5056: 5053: 5051: 5048: 5046: 5043: 5042: 5037: 5033: 5029: 5026: 5024: 5021: 5019: 5016: 5014: 5011: 5010: 5008: 5003: 5000: 4997: 4994: 4988: 4959: 4958: 4947: 4944: 4941: 4938: 4934: 4928: 4920: 4916: 4912: 4908: 4904: 4900: 4896: 4892: 4888: 4884: 4880: 4876: 4875: 4873: 4868: 4865: 4862: 4859: 4855: 4843: 4842: 4831: 4828: 4825: 4821: 4815: 4809: 4806: 4805: 4802: 4799: 4798: 4795: 4792: 4791: 4788: 4785: 4784: 4782: 4777: 4774: 4771: 4768: 4764: 4758: 4750: 4746: 4742: 4739: 4735: 4731: 4727: 4724: 4720: 4716: 4712: 4709: 4705: 4701: 4697: 4694: 4693: 4690: 4687: 4685: 4682: 4680: 4677: 4675: 4672: 4671: 4668: 4665: 4663: 4660: 4658: 4655: 4653: 4650: 4649: 4646: 4643: 4641: 4638: 4636: 4633: 4631: 4628: 4627: 4625: 4620: 4617: 4614: 4611: 4605: 4601: 4583: 4582: 4571: 4563: 4559: 4555: 4552: 4547: 4543: 4539: 4534: 4530: 4524: 4520: 4516: 4511: 4507: 4501: 4497: 4493: 4488: 4484: 4476: 4472: 4468: 4465: 4460: 4456: 4452: 4447: 4443: 4437: 4433: 4429: 4424: 4420: 4414: 4410: 4403: 4400: 4397: 4394: 4362:Main article: 4359: 4356: 4334: 4331: 4328: 4308: 4305: 4302: 4298: 4288:Consequently, 4286: 4285: 4272: 4268: 4264: 4258: 4255: 4251: 4246: 4242: 4238: 4234: 4231: 4227: 4223: 4220: 4217: 4214: 4210: 4195: 4194: 4183: 4180: 4177: 4173: 4169: 4166: 4163: 4159: 4155: 4152: 4149: 4146: 4142: 4110: 4107: 4104: 4101: 4097: 4093: 4090: 4087: 4084: 4081: 4078: 4075: 4072: 4069: 4040: 4036: 4033: 4030: 4027: 4023: 4011: 4010: 3999: 3996: 3993: 3990: 3986: 3981: 3977: 3974: 3971: 3968: 3965: 3961: 3956: 3950: 3947: 3943: 3938: 3934: 3930: 3926: 3923: 3920: 3917: 3914: 3911: 3907: 3901: 3898: 3894: 3889: 3885: 3881: 3877: 3874: 3871: 3867: 3863: 3860: 3857: 3854: 3850: 3835: 3834: 3823: 3820: 3817: 3814: 3810: 3805: 3801: 3798: 3795: 3792: 3788: 3783: 3779: 3776: 3773: 3770: 3766: 3742: 3739: 3736: 3732: 3720: 3719: 3708: 3705: 3702: 3699: 3695: 3690: 3684: 3681: 3677: 3672: 3668: 3664: 3660: 3657: 3654: 3651: 3648: 3645: 3641: 3635: 3632: 3628: 3623: 3619: 3615: 3611: 3608: 3605: 3602: 3599: 3596: 3592: 3577: 3576: 3565: 3562: 3559: 3555: 3550: 3546: 3543: 3540: 3537: 3533: 3529: 3526: 3523: 3520: 3516: 3512: 3508: 3504: 3500: 3496: 3493: 3470: 3467: 3464: 3460: 3448: 3447: 3436: 3433: 3430: 3427: 3423: 3418: 3414: 3411: 3408: 3405: 3401: 3396: 3392: 3389: 3386: 3383: 3379: 3375: 3372: 3369: 3366: 3362: 3358: 3344: 3343: 3332: 3329: 3326: 3322: 3317: 3313: 3310: 3307: 3304: 3300: 3295: 3291: 3288: 3285: 3282: 3276: 3272: 3242: 3239: 3238: 3237: 3226: 3223: 3220: 3215: 3207: 3204: 3201: 3196: 3190: 3186: 3185: 3182: 3179: 3178: 3174: 3169: 3165: 3164: 3160: 3156: 3155: 3153: 3148: 3145: 3119:Main article: 3116: 3113: 3101: 3100: 3089: 3086: 3083: 3078: 3071: 3065: 3062: 3059: 3054: 3049: 3047: 3044: 3041: 3035: 3030: 3025: 3022: 3017: 3013: 3010: 3006: 3005: 3003: 2998: 2995: 2982:if and only if 2970:Main article: 2967: 2964: 2932: 2929: 2926: 2881: 2880: 2869: 2865: 2860: 2856: 2852: 2848: 2844: 2840: 2837: 2834: 2831: 2828: 2804: 2800: 2796: 2792: 2773: 2772: 2761: 2755: 2750: 2746: 2742: 2739: 2736: 2733: 2728: 2724: 2720: 2717: 2714: 2711: 2706: 2702: 2698: 2695: 2692: 2689: 2684: 2680: 2676: 2673: 2670: 2665: 2660: 2656: 2652: 2649: 2646: 2643: 2638: 2634: 2630: 2627: 2624: 2621: 2616: 2612: 2608: 2605: 2602: 2596: 2593: 2590: 2587: 2584: 2549: 2539:of the matrix 2528: 2525: 2522: 2521: 2510: 2507: 2504: 2500: 2495: 2491: 2488: 2485: 2482: 2478: 2473: 2469: 2466: 2463: 2460: 2456: 2435: 2432: 2429: 2425: 2420: 2416: 2413: 2410: 2407: 2403: 2398: 2394: 2391: 2388: 2385: 2381: 2377: 2374: 2371: 2368: 2365: 2361: 2357: 2347: 2338: 2337: 2326: 2323: 2320: 2316: 2311: 2307: 2304: 2301: 2298: 2294: 2289: 2285: 2282: 2279: 2276: 2272: 2251: 2248: 2245: 2241: 2236: 2232: 2229: 2226: 2223: 2219: 2214: 2210: 2207: 2204: 2201: 2197: 2193: 2190: 2187: 2184: 2180: 2176: 2166: 2161:Laplace domain 2157: 2156: 2145: 2142: 2139: 2135: 2131: 2128: 2125: 2121: 2117: 2114: 2111: 2108: 2104: 2100: 2097: 2094: 2090: 2086: 2083: 2080: 2077: 2073: 2052: 2049: 2046: 2042: 2038: 2035: 2032: 2028: 2024: 2021: 2018: 2015: 2011: 2007: 2004: 2001: 1997: 1993: 1990: 1987: 1984: 1981: 1978: 1974: 1963: 1959: 1958: 1947: 1944: 1941: 1937: 1932: 1928: 1925: 1922: 1919: 1915: 1910: 1906: 1903: 1900: 1897: 1893: 1872: 1869: 1866: 1862: 1857: 1853: 1850: 1847: 1844: 1840: 1835: 1831: 1828: 1825: 1822: 1819: 1816: 1812: 1801: 1797: 1796: 1785: 1782: 1779: 1775: 1771: 1768: 1765: 1761: 1757: 1754: 1751: 1748: 1744: 1740: 1737: 1734: 1730: 1726: 1723: 1720: 1717: 1713: 1692: 1689: 1686: 1682: 1678: 1675: 1672: 1668: 1664: 1661: 1658: 1655: 1651: 1647: 1644: 1641: 1637: 1633: 1630: 1627: 1624: 1618: 1614: 1600: 1596: 1595: 1584: 1581: 1578: 1574: 1569: 1565: 1562: 1559: 1556: 1552: 1547: 1543: 1540: 1537: 1534: 1530: 1509: 1506: 1503: 1499: 1494: 1490: 1487: 1484: 1481: 1477: 1472: 1468: 1465: 1462: 1459: 1453: 1449: 1435: 1431: 1430: 1425: 1414:Hybrid systems 1401: 1381: 1360: 1356: 1353: 1332: 1328: 1325: 1305: 1290: 1289: 1277: 1274: 1271: 1267: 1260: 1257: 1253: 1248: 1245: 1242: 1239: 1233: 1229: 1215: 1203: 1200: 1197: 1194: 1191: 1188: 1185: 1182: 1178: 1174: 1171: 1168: 1148: 1145: 1142: 1138: 1117: 1114: 1111: 1107: 1096: 1084: 1081: 1078: 1075: 1072: 1069: 1066: 1063: 1059: 1055: 1052: 1049: 1029: 1026: 1023: 1019: 1008: 996: 993: 990: 987: 984: 981: 978: 975: 971: 967: 964: 961: 941: 938: 935: 931: 920: 908: 905: 902: 899: 896: 893: 890: 887: 883: 879: 876: 873: 853: 850: 847: 843: 832: 818: 813: 808: 805: 802: 799: 795: 774: 771: 768: 764: 753: 739: 734: 729: 726: 723: 720: 716: 695: 692: 689: 685: 674: 660: 655: 650: 647: 644: 641: 637: 616: 613: 610: 606: 591: 590: 579: 576: 573: 569: 565: 562: 559: 555: 551: 548: 545: 542: 538: 534: 531: 528: 524: 520: 517: 514: 511: 507: 496: 485: 482: 479: 475: 471: 468: 465: 461: 457: 454: 451: 448: 444: 440: 437: 434: 430: 426: 423: 420: 417: 411: 407: 380: 360: 340: 320: 319:Linear systems 317: 296: 280: 277: 241: 238: 235: 215: 195: 88: 87: 42: 40: 33: 26: 9: 6: 4: 3: 2: 12592: 12581: 12578: 12576: 12573: 12571: 12568: 12566: 12563: 12562: 12560: 12543: 12540: 12538: 12535: 12534: 12527: 12523: 12520: 12518: 12515: 12514: 12511: 12507: 12506: 12503: 12497: 12494: 12492: 12489: 12487: 12484: 12482: 12479: 12477: 12474: 12472: 12469: 12467: 12464: 12462: 12459: 12457: 12454: 12452: 12449: 12447: 12444: 12442: 12439: 12437: 12434: 12432: 12429: 12427: 12424: 12423: 12421: 12419:Architectures 12417: 12411: 12408: 12406: 12403: 12401: 12398: 12396: 12393: 12391: 12388: 12386: 12383: 12381: 12378: 12376: 12373: 12371: 12368: 12367: 12365: 12363:Organizations 12361: 12355: 12352: 12350: 12347: 12345: 12342: 12340: 12337: 12335: 12332: 12330: 12327: 12325: 12322: 12320: 12317: 12315: 12312: 12310: 12307: 12305: 12302: 12300: 12299:Yoshua Bengio 12297: 12296: 12294: 12290: 12280: 12279:Robot control 12277: 12273: 12270: 12269: 12268: 12265: 12263: 12260: 12258: 12255: 12253: 12250: 12248: 12245: 12243: 12240: 12238: 12235: 12233: 12230: 12229: 12227: 12223: 12217: 12214: 12212: 12209: 12207: 12204: 12202: 12199: 12197: 12196:Chinchilla AI 12194: 12192: 12189: 12187: 12184: 12182: 12179: 12177: 12174: 12172: 12169: 12167: 12164: 12162: 12159: 12157: 12154: 12152: 12149: 12147: 12144: 12142: 12139: 12135: 12132: 12131: 12130: 12127: 12125: 12122: 12120: 12117: 12115: 12112: 12110: 12107: 12105: 12102: 12101: 12099: 12095: 12089: 12086: 12082: 12079: 12077: 12074: 12073: 12072: 12069: 12065: 12062: 12060: 12057: 12055: 12052: 12051: 12050: 12047: 12045: 12042: 12040: 12037: 12035: 12032: 12030: 12027: 12025: 12022: 12020: 12017: 12015: 12012: 12010: 12007: 12005: 12002: 12001: 11999: 11995: 11992: 11988: 11982: 11979: 11977: 11974: 11972: 11969: 11967: 11964: 11962: 11959: 11957: 11954: 11952: 11949: 11948: 11946: 11942: 11936: 11933: 11931: 11928: 11926: 11923: 11921: 11918: 11916: 11913: 11912: 11910: 11906: 11898: 11895: 11894: 11893: 11890: 11888: 11885: 11883: 11880: 11876: 11875:Deep learning 11873: 11872: 11871: 11868: 11864: 11861: 11860: 11859: 11856: 11855: 11853: 11849: 11843: 11840: 11838: 11835: 11831: 11828: 11827: 11826: 11823: 11821: 11818: 11814: 11811: 11809: 11806: 11804: 11801: 11800: 11799: 11796: 11794: 11791: 11789: 11786: 11784: 11781: 11779: 11776: 11774: 11771: 11769: 11766: 11764: 11763:Hallucination 11761: 11757: 11754: 11753: 11752: 11749: 11747: 11744: 11740: 11737: 11736: 11735: 11732: 11731: 11729: 11725: 11719: 11716: 11714: 11711: 11709: 11706: 11704: 11701: 11699: 11696: 11694: 11691: 11689: 11686: 11684: 11681: 11679: 11678: 11674: 11673: 11671: 11669: 11665: 11656: 11651: 11649: 11644: 11642: 11637: 11636: 11633: 11626: 11622: 11618: 11614: 11611: 11610: 11598: 11592: 11588: 11583: 11582: 11578: 11575: 11574: 11568: 11562: 11558: 11553: 11549: 11547:0-486-44278-0 11543: 11539: 11534: 11523: 11521:0-387-98489-5 11517: 11510: 11509: 11503: 11499: 11493: 11489: 11484: 11480: 11478:0-13-067389-7 11474: 11470: 11465: 11461: 11459:0-19-511777-8 11455: 11451: 11446: 11442: 11436: 11432: 11427: 11426: 11412: 11405: 11397: 11391: 11387: 11380: 11373: 11367: 11359: 11355: 11351: 11347: 11343: 11339: 11335: 11331: 11327: 11320: 11313: 11307: 11303: 11299: 11295: 11288: 11280: 11276: 11272: 11268: 11263: 11258: 11254: 11250: 11246: 11242: 11235: 11228: 11222: 11214: 11210: 11206: 11202: 11198: 11194: 11190: 11186: 11182: 11178: 11171: 11163: 11159: 11155: 11151: 11147: 11143: 11136: 11128: 11124: 11120: 11114: 11110: 11103: 11096: 11090: 11086: 11082: 11078: 11071: 11062: 11057: 11053: 11049: 11045: 11038: 11030: 11024: 11020: 11019: 11011: 11003: 10997: 10993: 10992: 10987: 10981: 10977: 10966: 10965:Kalman filter 10963: 10960: 10957: 10954: 10951: 10948: 10945: 10943: 10940: 10938: 10937:Observability 10935: 10933: 10930: 10928: 10925: 10923: 10920: 10919: 10912: 10910: 10907:for integers 10889: 10883: 10876: 10873: 10867: 10862: 10857: 10849: 10845: 10835: 10831: 10824: 10815: 10814: 10813: 10799: 10796: 10790: 10787: 10776: 10772: 10753: 10748: 10739: 10730: 10726: 10718: 10715: 10711: 10706: 10700: 10691: 10687: 10682: 10679: 10674: 10671: 10666: 10656: 10648: 10644: 10637: 10632: 10623: 10617: 10614: 10611: 10600: 10595: 10586: 10578: 10571: 10568: 10554: 10546: 10539: 10536: 10526: 10521: 10515: 10506: 10491: 10490: 10489: 10469: 10462: 10459: 10452: 10447: 10440: 10437: 10426: 10408: 10400: 10393: 10390: 10383: 10377: 10369: 10365: 10357: 10339: 10333: 10330: 10324: 10316: 10312: 10304: 10303: 10302: 10282: 10273: 10269: 10261: 10258: 10254: 10249: 10243: 10234: 10230: 10225: 10222: 10217: 10214: 10209: 10206: 10200: 10192: 10185: 10182: 10171: 10154: 10146: 10142: 10138: 10132: 10124: 10117: 10114: 10103: 10102: 10101: 10083: 10063: 10056: 10041: 10034: 10019: 10012: 9997: 9990: 9972: 9966: 9959: 9958: 9957: 9937: 9928: 9925: 9919: 9916: 9913: 9907: 9901: 9898: 9895: 9892: 9889: 9886: 9883: 9880: 9874: 9865: 9862: 9854: 9850: 9846: 9839: 9838: 9837: 9836: 9826: 9809: 9803: 9780: 9777: 9774: 9771: 9768: 9762: 9733: 9727: 9724: 9718: 9712: 9709: 9706: 9695: 9689: 9674: 9654: 9648: 9645: 9639: 9633: 9630: 9627: 9616: 9610: 9588: 9587: 9586: 9578: 9559: 9553: 9548: 9541: 9536: 9530: 9525: 9520: 9512: 9504: 9501: 9496: 9489: 9486: 9481: 9474: 9469: 9463: 9456: 9450: 9445: 9439: 9428: 9422: 9417: 9411: 9403: 9398: 9393: 9387: 9384: 9377: 9371: 9362: 9361: 9360: 9359:test is then 9358: 9357:observability 9353: 9339: 9319: 9299: 9276: 9267: 9264: 9238: 9229: 9226: 9200: 9194: 9174: 9154: 9129: 9119: 9115: 9111: 9106: 9099: 9096: 9085: 9082: 9075: 9069: 9064: 9059: 9051: 9043: 9040: 9031: 9025: 9018: 9010: 9007: 9002: 8995: 8992: 8987: 8980: 8975: 8969: 8960: 8952: 8949: 8940: 8934: 8926: 8921: 8916: 8910: 8907: 8902: 8896: 8887: 8886: 8885: 8884:test is then 8883: 8860: 8844: 8826: 8818: 8811: 8808: 8801: 8795: 8787: 8780: 8777: 8766: 8748: 8740: 8733: 8730: 8723: 8717: 8709: 8705: 8697: 8679: 8671: 8667: 8659: 8658: 8657: 8639: 8629: 8604: 8582: 8577: 8570: 8565: 8558: 8554: 8548: 8533: 8516: 8503: 8495: 8492: 8483: 8477: 8472: 8467: 8458: 8450: 8433: 8425: 8412: 8405: 8397: 8394: 8389: 8382: 8379: 8374: 8367: 8362: 8356: 8351: 8346: 8337: 8329: 8322: 8303: 8295: 8288: 8273: 8264: 8263: 8262: 8244: 8237: 8222: 8215: 8200: 8193: 8175: 8169: 8162: 8144: 8135: 8132: 8122:is velocity; 8106: 8097: 8094: 8084:is position; 8068: 8062: 8055: 8054: 8053: 8033: 8027: 8024: 8021: 8015: 8006: 8003: 7997: 7994: 7988: 7982: 7979: 7973: 7964: 7961: 7955: 7948: 7947: 7946: 7944: 7917: 7906: 7903: 7897: 7882: 7865: 7854: 7851: 7845: 7833: 7829: 7826: 7823: 7820: 7817: 7813: 7809: 7803: 7794: 7779: 7778: 7777: 7775: 7753: 7742: 7737: 7734: 7729: 7725: 7722: 7719: 7716: 7712: 7707: 7701: 7690: 7685: 7682: 7677: 7673: 7670: 7667: 7664: 7660: 7655: 7649: 7634: 7617: 7605: 7601: 7596: 7593: 7588: 7584: 7581: 7578: 7575: 7571: 7566: 7563: 7560: 7556: 7552: 7549: 7543: 7531: 7527: 7522: 7519: 7514: 7510: 7507: 7504: 7501: 7497: 7492: 7489: 7486: 7483: 7479: 7475: 7469: 7460: 7445: 7444: 7443: 7426: 7392: 7381: 7378: 7372: 7361: 7358: 7355: 7349: 7338: 7335: 7329: 7314: 7297: 7286: 7283: 7277: 7266: 7263: 7260: 7254: 7243: 7240: 7234: 7225: 7210: 7209: 7208: 7188: 7177: 7174: 7168: 7157: 7154: 7148: 7133: 7116: 7105: 7102: 7096: 7085: 7082: 7076: 7067: 7052: 7051: 7050: 7033: 7022: 7016: 7005: 7002: 6999: 6993: 6962: 6956: 6943: 6934: 6920: 6917: 6914: 6911: 6885: 6874: 6868: 6853: 6836: 6824: 6820: 6817: 6814: 6811: 6807: 6803: 6797: 6788: 6773: 6772: 6771: 6769: 6765: 6761: 6757: 6753: 6749: 6739: 6737: 6733: 6729: 6712: 6708: 6703: 6700: 6695: 6691: 6688: 6685: 6682: 6678: 6673: 6670: 6667: 6664: 6660: 6651: 6647: 6643: 6621: 6610: 6605: 6602: 6597: 6593: 6590: 6587: 6584: 6580: 6575: 6569: 6554: 6537: 6525: 6521: 6516: 6513: 6508: 6504: 6501: 6498: 6495: 6491: 6486: 6483: 6480: 6477: 6473: 6469: 6463: 6454: 6439: 6438: 6437: 6420: 6386: 6375: 6372: 6369: 6363: 6352: 6349: 6343: 6328: 6311: 6300: 6297: 6294: 6288: 6277: 6274: 6268: 6259: 6244: 6243: 6242: 6222: 6211: 6208: 6202: 6191: 6188: 6182: 6167: 6150: 6139: 6136: 6130: 6119: 6116: 6110: 6101: 6086: 6085: 6084: 6082: 6078: 6059: 6048: 6045: 6039: 6023: 6014: 6005: 5952: 5937: 5931: 5925: 5920: 5914: 5899: 5893: 5888: 5882: 5877: 5871: 5854: 5853: 5835: 5820: 5814: 5807: 5801: 5796: 5790: 5775: 5769: 5764: 5757: 5754: 5749: 5746: 5740: 5735: 5729: 5720: 5705: 5704: 5703: 5686: 5683: 5677: 5674: 5671: 5668: 5665: 5660: 5656: 5650: 5647: 5644: 5638: 5632: 5629: 5626: 5623: 5620: 5615: 5611: 5605: 5602: 5599: 5596: 5593: 5588: 5584: 5577: 5571: 5554: 5553: 5552: 5549: 5547: 5543: 5539: 5535: 5516: 5487: 5481: 5448: 5429: 5423: 5398: 5392: 5375: 5374: 5373: 5371: 5367: 5357: 5355: 5336: 5330: 5315: 5309: 5304: 5299: 5294: 5288: 5283: 5277: 5260: 5259: 5241: 5226: 5218: 5214: 5204: 5200: 5190: 5186: 5176: 5172: 5165: 5160: 5154: 5139: 5131: 5127: 5123: 5118: 5113: 5108: 5099: 5095: 5091: 5086: 5081: 5076: 5067: 5063: 5059: 5054: 5049: 5044: 5035: 5031: 5027: 5022: 5017: 5012: 5006: 5001: 4995: 4986: 4971: 4970: 4969: 4966: 4964: 4945: 4939: 4926: 4918: 4914: 4906: 4902: 4894: 4890: 4882: 4878: 4871: 4866: 4860: 4845: 4844: 4826: 4813: 4807: 4800: 4793: 4786: 4780: 4775: 4769: 4756: 4748: 4744: 4740: 4733: 4729: 4725: 4718: 4714: 4710: 4703: 4699: 4695: 4688: 4683: 4678: 4673: 4666: 4661: 4656: 4651: 4644: 4639: 4634: 4629: 4623: 4618: 4612: 4603: 4588: 4587: 4586: 4569: 4561: 4557: 4553: 4550: 4545: 4541: 4537: 4532: 4528: 4522: 4518: 4514: 4509: 4505: 4499: 4495: 4491: 4486: 4482: 4474: 4470: 4466: 4463: 4458: 4454: 4450: 4445: 4441: 4435: 4431: 4427: 4422: 4418: 4412: 4408: 4401: 4395: 4378: 4377: 4376: 4373: 4371: 4365: 4355: 4353: 4349: 4332: 4329: 4326: 4303: 4266: 4256: 4253: 4240: 4232: 4221: 4215: 4200: 4199: 4198: 4178: 4164: 4153: 4147: 4132: 4131: 4130: 4128: 4124: 4105: 4099: 4095: 4088: 4082: 4079: 4073: 4067: 4059: 4055: 4034: 4028: 3997: 3991: 3975: 3966: 3948: 3945: 3932: 3924: 3918: 3912: 3899: 3896: 3883: 3875: 3861: 3855: 3840: 3839: 3838: 3821: 3815: 3799: 3793: 3777: 3771: 3756: 3755: 3754: 3737: 3706: 3700: 3682: 3679: 3666: 3658: 3652: 3646: 3633: 3630: 3617: 3609: 3603: 3597: 3582: 3581: 3580: 3560: 3544: 3538: 3527: 3521: 3502: 3494: 3484: 3483: 3482: 3465: 3434: 3428: 3412: 3406: 3390: 3384: 3373: 3367: 3356: 3349: 3348: 3347: 3327: 3311: 3305: 3289: 3283: 3274: 3259: 3258: 3257: 3255: 3250: 3248: 3224: 3221: 3218: 3213: 3205: 3202: 3199: 3180: 3151: 3146: 3143: 3136: 3135: 3134: 3132: 3127: 3122: 3121:Observability 3115:Observability 3112: 3110: 3106: 3087: 3084: 3081: 3076: 3063: 3060: 3057: 3045: 3033: 3001: 2996: 2993: 2986: 2985: 2984: 2983: 2980: 2973: 2963: 2961: 2957: 2953: 2948: 2946: 2945:minimum phase 2927: 2908: 2906: 2902: 2898: 2894: 2893:singularities 2890: 2886: 2867: 2854: 2846: 2838: 2832: 2826: 2819: 2818: 2817: 2798: 2790: 2782: 2778: 2759: 2748: 2744: 2740: 2737: 2726: 2722: 2718: 2715: 2704: 2700: 2696: 2693: 2682: 2678: 2674: 2671: 2658: 2654: 2650: 2647: 2636: 2632: 2628: 2625: 2614: 2610: 2606: 2603: 2594: 2591: 2585: 2568: 2567: 2566: 2564: 2538: 2534: 2505: 2489: 2483: 2467: 2461: 2430: 2414: 2408: 2392: 2386: 2375: 2372: 2366: 2355: 2348: 2343: 2340: 2321: 2305: 2299: 2283: 2277: 2246: 2230: 2224: 2208: 2202: 2191: 2185: 2174: 2167: 2162: 2159: 2140: 2126: 2115: 2109: 2095: 2084: 2078: 2047: 2033: 2022: 2016: 2002: 1991: 1985: 1982: 1979: 1964: 1961: 1942: 1926: 1920: 1904: 1898: 1867: 1851: 1845: 1829: 1823: 1820: 1817: 1802: 1799: 1780: 1766: 1755: 1749: 1735: 1724: 1718: 1687: 1673: 1662: 1656: 1642: 1631: 1625: 1616: 1601: 1598: 1579: 1563: 1557: 1541: 1535: 1504: 1488: 1482: 1466: 1460: 1451: 1436: 1433: 1429: 1426: 1424: 1421: 1417: 1415: 1399: 1379: 1354: 1351: 1326: 1323: 1303: 1295: 1272: 1258: 1255: 1251: 1246: 1240: 1231: 1216: 1201: 1198: 1195: 1192: 1183: 1169: 1166: 1143: 1112: 1097: 1082: 1079: 1076: 1073: 1064: 1050: 1047: 1024: 1009: 994: 991: 988: 985: 976: 962: 959: 936: 921: 906: 903: 900: 897: 888: 874: 871: 848: 833: 816: 806: 800: 769: 754: 737: 727: 721: 690: 675: 658: 648: 642: 611: 596: 595: 594: 574: 560: 549: 543: 529: 518: 512: 497: 480: 466: 455: 449: 435: 424: 418: 409: 394: 393: 392: 378: 358: 338: 325: 316: 314: 310: 294: 286: 283:The internal 276: 274: 273:Kalman Filter 269: 265: 260: 258: 254: 239: 236: 233: 213: 193: 185: 181: 177: 176:system theory 173: 169: 165: 160: 158: 154: 150: 146: 145: 140: 135: 133: 129: 125: 121: 117: 113: 109: 105: 99: 95: 84: 81: 73: 63: 59: 53: 52: 46: 41: 32: 31: 19: 12385:Hugging Face 12349:David Silver 11997:Audio–visual 11851:Applications 11830:Augmentation 11675: 11586: 11556: 11537: 11525:. Retrieved 11507: 11490:. Springer. 11487: 11468: 11449: 11430: 11410: 11404: 11385: 11379: 11371: 11366: 11336:(1): 35–45. 11333: 11329: 11319: 11293: 11287: 11262:10419/153623 11244: 11240: 11234: 11221: 11180: 11176: 11170: 11145: 11141: 11135: 11108: 11102: 11076: 11070: 11051: 11047: 11037: 11017: 11010: 10990: 10980: 10908: 10906: 10768: 10487: 10300: 10099: 9955: 9832: 9754: 9584: 9576: 9354: 9146: 8879: 8655: 8260: 8051: 7940: 7773: 7771: 7410: 7206: 6948: 6903: 6763: 6759: 6755: 6751: 6747: 6745: 6735: 6731: 6728:controllable 6649: 6645: 6639: 6404: 6240: 6076: 6021: 6019: 5970: 5701: 5550: 5545: 5541: 5537: 5533: 5463: 5363: 5353: 5351: 4967: 4962: 4960: 4584: 4374: 4367: 4287: 4196: 4012: 3836: 3721: 3578: 3449: 3345: 3251: 3244: 3130: 3128: 3124: 3108: 3102: 2979:controllable 2978: 2975: 2951: 2949: 2909: 2882: 2774: 2530: 1427: 1422: 1291: 592: 371:outputs and 330: 282: 264:econometrics 261: 161: 157:state vector 156: 142: 138: 136: 131: 111: 101: 76: 67: 48: 12533:Categories 12481:Autoencoder 12436:Transformer 12304:Alex Graves 12252:OpenAI Five 12156:IBM Watsonx 11778:Convolution 11756:Overfitting 11148:(1): 1–10. 10959:State space 10953:Phase space 10771:equilibrium 8845:the output 6642:eigenvalues 2956:BIBO stable 2891:(i.e., the 2885:eigenvalues 2781:determinant 2537:eigenvalues 1423:System type 268:time series 206:inputs and 184:time-domain 144:phase space 139:state space 62:introducing 12559:Categories 12522:Technology 12375:EleutherAI 12334:Fei-Fei Li 12329:Yann LeCun 12242:Q-learning 12225:Decisional 12151:IBM Watson 12059:Midjourney 11951:TensorFlow 11798:Activation 11751:Regression 11746:Clustering 10973:References 3131:observable 2533:LTI system 309:capacitors 92:See also: 45:references 12405:MIT CSAIL 12370:Anthropic 12339:Andrew Ng 12237:AlphaZero 12081:VideoPoet 12044:AlphaFold 11981:MindSpore 11935:SpiNNaker 11930:Memristor 11837:Diffusion 11813:Rectifier 11793:Batchnorm 11773:Attention 11768:Adversary 11540:. Dover. 11358:259115248 11350:0021-9223 11271:0883-7252 11197:0899-7667 11162:0018-9286 11127:794591362 10877:π 10791:˙ 10719:ℓ 10707:− 10683:⁡ 10675:ℓ 10667:− 10572:˙ 10540:˙ 10507:˙ 10463:¨ 10441:˙ 10394:˙ 10334:θ 10262:ℓ 10250:− 10226:⁡ 10218:ℓ 10210:− 10186:˙ 10118:˙ 10064:ℓ 9967:θ 9929:˙ 9926:θ 9920:ℓ 9914:− 9902:θ 9899:⁡ 9890:ℓ 9884:− 9866:¨ 9863:θ 9851:ℓ 9781:⋅ 9775:⋅ 9769:⋅ 9602:˙ 9497:− 9482:− 9268:¨ 9230:˙ 9107:− 9003:− 8988:− 8812:¨ 8781:˙ 8734:˙ 8390:− 8375:− 8323:˙ 8289:˙ 8136:¨ 8098:˙ 8022:− 8007:˙ 7995:− 7965:¨ 7821:− 7795:˙ 7735:− 7683:− 7594:− 7564:− 7520:− 7487:− 7461:˙ 7356:− 7261:− 7226:˙ 7068:˙ 7003:− 6789:˙ 6701:− 6686:− 6603:− 6588:− 6514:− 6499:− 6455:˙ 6260:˙ 6102:˙ 5989:∞ 5755:− 5747:− 5721:˙ 5501:∞ 5443:∞ 5368:(and not 5124:− 5092:− 5060:− 5028:− 4987:˙ 4741:− 4726:− 4711:− 4696:− 4604:˙ 4330:× 4254:− 4241:− 3946:− 3933:− 3897:− 3884:− 3680:− 3667:− 3631:− 3618:− 3579:and thus 3503:− 3481:, giving 3374:− 3275:˙ 3203:− 3181:⋮ 3147:⁡ 3061:− 3046:⋯ 2997:⁡ 2960:removable 2855:− 2827:λ 2799:− 2741:− 2719:− 2697:− 2675:− 2651:− 2629:− 2607:− 2373:− 2192:− 1617:˙ 1452:˙ 1355:∈ 1327:∈ 1232:˙ 1199:× 1184:⋅ 1170:⁡ 1144:⋅ 1113:⋅ 1080:× 1065:⋅ 1051:⁡ 1025:⋅ 992:× 977:⋅ 963:⁡ 937:⋅ 904:× 889:⋅ 875:⁡ 849:⋅ 807:∈ 770:⋅ 728:∈ 691:⋅ 649:∈ 612:⋅ 410:˙ 313:inductors 237:× 120:variables 12513:Portals 12272:Auto-GPT 12104:Word2vec 11908:Hardware 11825:Datasets 11727:Concepts 11527:June 28, 11279:14231301 11213:10020032 11205:12803953 10915:See also 9835:pendulum 7207:becomes 6241:becomes 6008:Feedback 4121:. For a 2342:Z-domain 351:inputs, 70:May 2009 12395:Meta AI 12232:AlphaGo 12216:PanGu-ÎŁ 12186:ChatGPT 12161:Granite 12109:Seq2seq 12088:Whisper 12009:WaveNet 12004:AlexNet 11976:Flux.jl 11956:PyTorch 11808:Sigmoid 11803:Softmax 11668:General 6742:Example 3837:giving 3346:yields 593:where: 162:If the 147:is the 58:improve 12410:Huawei 12390:OpenAI 12292:People 12262:MuZero 12124:Gemini 12119:Claude 12054:DALL-E 11966:Theano 11623:, and 11593:  11563:  11544:  11518:  11494:  11475:  11456:  11437:  11392:  11356:  11348:  11308:  11277:  11269:  11211:  11203:  11195:  11160:  11125:  11115:  11091:  11025:  10998:  10301:where 9956:where 8656:where 8052:where 6766:, the 5366:proper 4056:, the 4052:and a 3103:where 172:matrix 155:, the 153:vector 47:, but 12476:Mamba 12247:SARSA 12211:LLaMA 12206:BLOOM 12191:GPT-J 12181:GPT-4 12176:GPT-3 12171:GPT-2 12166:GPT-1 12129:LaMDA 11961:Keras 11512:(PDF) 11354:S2CID 11275:S2CID 11209:S2CID 3245:The " 2954:(see 2889:poles 114:is a 12400:Mila 12201:PaLM 12134:Bard 12114:BERT 12097:Text 12076:Sora 11591:ISBN 11561:ISBN 11542:ISBN 11529:2012 11516:ISBN 11492:ISBN 11473:ISBN 11454:ISBN 11435:ISBN 11390:ISBN 11346:ISSN 11306:ISBN 11267:ISSN 11201:PMID 11193:ISSN 11158:ISSN 11123:OCLC 11113:ISBN 11089:ISBN 11023:ISBN 10996:ISBN 10769:The 9355:The 9312:and 9167:and 8880:The 5540:and 3256:of 3144:rank 3105:rank 2994:rank 311:and 137:The 110:, a 106:and 96:and 12141:NMT 12024:OCR 12019:HWR 11971:JAX 11925:VPU 11920:TPU 11915:IPU 11739:SGD 11338:doi 11298:doi 11257:hdl 11249:doi 11185:doi 11150:doi 11081:doi 11056:doi 10680:sin 10223:sin 9896:sin 6644:of 2962:). 2899:or 2783:of 1294:LTI 1167:dim 1048:dim 960:dim 872:dim 141:or 126:or 102:In 12561:: 11619:, 11352:. 11344:. 11334:82 11332:. 11328:. 11304:, 11273:. 11265:. 11255:. 11245:29 11243:. 11207:. 11199:. 11191:. 11181:15 11179:. 11156:. 11146:20 11144:. 11121:. 11087:, 11052:15 11050:. 11046:. 10911:. 9254:, 9216:, 7049:. 6933:. 6762:= 6754:= 6738:. 5536:, 4354:. 2947:. 2907:. 2816:, 2344:of 2163:of 1412:. 1247::= 159:. 11654:e 11647:t 11640:v 11627:. 11599:. 11569:. 11550:. 11531:. 11500:. 11481:. 11462:. 11443:. 11398:. 11360:. 11340:: 11300:: 11281:. 11259:: 11251:: 11215:. 11187:: 11164:. 11152:: 11129:. 11083:: 11064:. 11058:: 11031:. 11004:. 10909:n 10890:] 10884:0 10874:n 10868:[ 10863:= 10858:] 10850:2 10846:x 10836:1 10832:x 10825:[ 10800:0 10797:= 10788:x 10773:/ 10754:. 10749:] 10743:) 10740:t 10737:( 10731:2 10727:x 10716:m 10712:k 10704:) 10701:t 10698:( 10692:1 10688:x 10672:g 10660:) 10657:t 10654:( 10649:2 10645:x 10638:[ 10633:= 10630:) 10627:) 10624:t 10621:( 10618:x 10615:, 10612:t 10609:( 10605:f 10601:= 10596:] 10590:) 10587:t 10584:( 10579:2 10569:x 10558:) 10555:t 10552:( 10547:1 10537:x 10527:[ 10522:= 10519:) 10516:t 10513:( 10503:x 10470:1 10460:x 10453:= 10448:2 10438:x 10412:) 10409:t 10406:( 10401:1 10391:x 10384:= 10381:) 10378:t 10375:( 10370:2 10366:x 10343:) 10340:t 10337:( 10331:= 10328:) 10325:t 10322:( 10317:1 10313:x 10286:) 10283:t 10280:( 10274:2 10270:x 10259:m 10255:k 10247:) 10244:t 10241:( 10235:1 10231:x 10215:g 10207:= 10204:) 10201:t 10198:( 10193:2 10183:x 10158:) 10155:t 10152:( 10147:2 10143:x 10139:= 10136:) 10133:t 10130:( 10125:1 10115:x 10096:) 10084:m 10042:k 10020:g 9998:m 9976:) 9973:t 9970:( 9941:) 9938:t 9935:( 9917:k 9911:) 9908:t 9905:( 9893:g 9887:m 9881:= 9878:) 9875:t 9872:( 9855:2 9847:m 9813:) 9810:t 9807:( 9804:u 9784:) 9778:, 9772:, 9766:( 9763:f 9740:) 9737:) 9734:t 9731:( 9728:u 9725:, 9722:) 9719:t 9716:( 9713:x 9710:, 9707:t 9704:( 9700:h 9696:= 9693:) 9690:t 9687:( 9683:y 9661:) 9658:) 9655:t 9652:( 9649:u 9646:, 9643:) 9640:t 9637:( 9634:x 9631:, 9628:t 9625:( 9621:f 9617:= 9614:) 9611:t 9608:( 9599:x 9560:] 9554:1 9549:0 9542:0 9537:1 9531:[ 9526:= 9521:] 9513:] 9505:m 9502:b 9490:m 9487:k 9475:1 9470:0 9464:[ 9457:] 9451:0 9446:1 9440:[ 9429:] 9423:0 9418:1 9412:[ 9404:[ 9399:= 9394:] 9388:A 9385:C 9378:C 9372:[ 9340:u 9320:m 9300:b 9280:) 9277:t 9274:( 9265:y 9242:) 9239:t 9236:( 9227:y 9204:) 9201:t 9198:( 9195:y 9175:m 9155:b 9130:] 9120:2 9116:m 9112:b 9100:m 9097:1 9086:m 9083:1 9076:0 9070:[ 9065:= 9060:] 9052:] 9044:m 9041:1 9032:0 9026:[ 9019:] 9011:m 9008:b 8996:m 8993:k 8981:1 8976:0 8970:[ 8961:] 8953:m 8950:1 8941:0 8935:[ 8927:[ 8922:= 8917:] 8911:B 8908:A 8903:B 8897:[ 8864:) 8861:t 8858:( 8854:y 8830:) 8827:t 8824:( 8819:1 8809:x 8802:= 8799:) 8796:t 8793:( 8788:2 8778:x 8752:) 8749:t 8746:( 8741:1 8731:x 8724:= 8721:) 8718:t 8715:( 8710:2 8706:x 8683:) 8680:t 8677:( 8672:1 8668:x 8640:] 8633:) 8630:t 8627:( 8621:2 8617:x 8608:) 8605:t 8602:( 8596:1 8592:x 8583:[ 8578:] 8571:0 8566:1 8559:[ 8555:= 8552:) 8549:t 8546:( 8542:y 8520:) 8517:t 8514:( 8510:u 8504:] 8496:m 8493:1 8484:0 8478:[ 8473:+ 8468:] 8462:) 8459:t 8456:( 8451:2 8446:x 8437:) 8434:t 8431:( 8426:1 8421:x 8413:[ 8406:] 8398:m 8395:b 8383:m 8380:k 8368:1 8363:0 8357:[ 8352:= 8347:] 8341:) 8338:t 8335:( 8330:2 8319:x 8307:) 8304:t 8301:( 8296:1 8285:x 8274:[ 8245:m 8223:k 8201:b 8179:) 8176:t 8173:( 8170:u 8148:) 8145:t 8142:( 8133:y 8110:) 8107:t 8104:( 8095:y 8072:) 8069:t 8066:( 8063:y 8037:) 8034:t 8031:( 8028:y 8025:k 8019:) 8016:t 8013:( 8004:y 7998:b 7992:) 7989:t 7986:( 7983:u 7980:= 7977:) 7974:t 7971:( 7962:y 7956:m 7921:) 7918:t 7915:( 7911:x 7907:C 7904:= 7901:) 7898:t 7895:( 7891:y 7869:) 7866:t 7863:( 7859:r 7855:B 7852:+ 7849:) 7846:t 7843:( 7839:x 7834:) 7830:C 7827:K 7824:B 7818:A 7814:( 7810:= 7807:) 7804:t 7801:( 7791:x 7774:D 7757:) 7754:t 7751:( 7747:r 7743:D 7738:1 7730:) 7726:K 7723:D 7720:+ 7717:I 7713:( 7708:+ 7705:) 7702:t 7699:( 7695:x 7691:C 7686:1 7678:) 7674:K 7671:D 7668:+ 7665:I 7661:( 7656:= 7653:) 7650:t 7647:( 7643:y 7621:) 7618:t 7615:( 7611:r 7606:) 7602:D 7597:1 7589:) 7585:K 7582:D 7579:+ 7576:I 7572:( 7567:K 7561:I 7557:( 7553:B 7550:+ 7547:) 7544:t 7541:( 7537:x 7532:) 7528:C 7523:1 7515:) 7511:K 7508:D 7505:+ 7502:I 7498:( 7493:K 7490:B 7484:A 7480:( 7476:= 7473:) 7470:t 7467:( 7457:x 7430:) 7427:t 7424:( 7420:y 7396:) 7393:t 7390:( 7386:r 7382:D 7379:+ 7376:) 7373:t 7370:( 7366:y 7362:K 7359:D 7353:) 7350:t 7347:( 7343:x 7339:C 7336:= 7333:) 7330:t 7327:( 7323:y 7301:) 7298:t 7295:( 7291:r 7287:B 7284:+ 7281:) 7278:t 7275:( 7271:y 7267:K 7264:B 7258:) 7255:t 7252:( 7248:x 7244:A 7241:= 7238:) 7235:t 7232:( 7222:x 7192:) 7189:t 7186:( 7182:u 7178:D 7175:+ 7172:) 7169:t 7166:( 7162:x 7158:C 7155:= 7152:) 7149:t 7146:( 7142:y 7120:) 7117:t 7114:( 7110:u 7106:B 7103:+ 7100:) 7097:t 7094:( 7090:x 7086:A 7083:= 7080:) 7077:t 7074:( 7064:x 7037:) 7034:t 7031:( 7027:r 7023:+ 7020:) 7017:t 7014:( 7010:y 7006:K 7000:= 6997:) 6994:t 6991:( 6987:u 6966:) 6963:t 6960:( 6957:r 6921:K 6918:B 6915:+ 6912:A 6889:) 6886:t 6883:( 6879:x 6875:= 6872:) 6869:t 6866:( 6862:y 6840:) 6837:t 6834:( 6830:x 6825:) 6821:K 6818:B 6815:+ 6812:A 6808:( 6804:= 6801:) 6798:t 6795:( 6785:x 6764:I 6760:C 6756:x 6752:y 6748:D 6736:K 6732:A 6713:) 6709:C 6704:1 6696:) 6692:K 6689:D 6683:I 6679:( 6674:K 6671:B 6668:+ 6665:A 6661:( 6650:K 6646:A 6625:) 6622:t 6619:( 6615:x 6611:C 6606:1 6598:) 6594:K 6591:D 6585:I 6581:( 6576:= 6573:) 6570:t 6567:( 6563:y 6541:) 6538:t 6535:( 6531:x 6526:) 6522:C 6517:1 6509:) 6505:K 6502:D 6496:I 6492:( 6487:K 6484:B 6481:+ 6478:A 6474:( 6470:= 6467:) 6464:t 6461:( 6451:x 6424:) 6421:t 6418:( 6414:y 6390:) 6387:t 6384:( 6380:y 6376:K 6373:D 6370:+ 6367:) 6364:t 6361:( 6357:x 6353:C 6350:= 6347:) 6344:t 6341:( 6337:y 6315:) 6312:t 6309:( 6305:y 6301:K 6298:B 6295:+ 6292:) 6289:t 6286:( 6282:x 6278:A 6275:= 6272:) 6269:t 6266:( 6256:x 6226:) 6223:t 6220:( 6216:u 6212:D 6209:+ 6206:) 6203:t 6200:( 6196:x 6192:C 6189:= 6186:) 6183:t 6180:( 6176:y 6154:) 6151:t 6148:( 6144:u 6140:B 6137:+ 6134:) 6131:t 6128:( 6124:x 6120:A 6117:= 6114:) 6111:t 6108:( 6098:x 6077:K 6063:) 6060:t 6057:( 6053:y 6049:K 6046:= 6043:) 6040:t 6037:( 6033:u 6022:K 5992:) 5986:( 5981:G 5956:) 5953:t 5950:( 5945:u 5938:] 5932:1 5926:[ 5921:+ 5918:) 5915:t 5912:( 5907:x 5900:] 5894:2 5889:1 5883:[ 5878:= 5875:) 5872:t 5869:( 5864:y 5839:) 5836:t 5833:( 5828:u 5821:] 5815:0 5808:1 5802:[ 5797:+ 5794:) 5791:t 5788:( 5783:x 5776:] 5770:0 5765:1 5758:1 5750:2 5741:[ 5736:= 5733:) 5730:t 5727:( 5717:x 5687:1 5684:+ 5678:1 5675:+ 5672:s 5669:2 5666:+ 5661:2 5657:s 5651:2 5648:+ 5645:s 5639:= 5633:1 5630:+ 5627:s 5624:2 5621:+ 5616:2 5612:s 5606:3 5603:+ 5600:s 5597:3 5594:+ 5589:2 5585:s 5578:= 5575:) 5572:s 5569:( 5564:G 5546:D 5542:C 5538:B 5534:A 5520:) 5517:t 5514:( 5509:u 5504:) 5498:( 5493:G 5488:= 5485:) 5482:t 5479:( 5474:y 5449:. 5446:) 5440:( 5435:G 5430:+ 5427:) 5424:s 5421:( 5415:P 5412:S 5405:G 5399:= 5396:) 5393:s 5390:( 5385:G 5337:. 5334:) 5331:t 5328:( 5323:x 5316:] 5310:1 5305:0 5300:0 5295:0 5289:[ 5284:= 5281:) 5278:t 5275:( 5270:y 5245:) 5242:t 5239:( 5234:u 5227:] 5219:1 5215:n 5205:2 5201:n 5191:3 5187:n 5177:4 5173:n 5166:[ 5161:+ 5158:) 5155:t 5152:( 5147:x 5140:] 5132:1 5128:d 5119:1 5114:0 5109:0 5100:2 5096:d 5087:0 5082:1 5077:0 5068:3 5064:d 5055:0 5050:0 5045:1 5036:4 5032:d 5023:0 5018:0 5013:0 5007:[ 5002:= 4999:) 4996:t 4993:( 4983:x 4946:. 4943:) 4940:t 4937:( 4933:x 4927:] 4919:1 4915:n 4907:2 4903:n 4895:3 4891:n 4883:4 4879:n 4872:[ 4867:= 4864:) 4861:t 4858:( 4854:y 4830:) 4827:t 4824:( 4820:u 4814:] 4808:1 4801:0 4794:0 4787:0 4781:[ 4776:+ 4773:) 4770:t 4767:( 4763:x 4757:] 4749:1 4745:d 4734:2 4730:d 4719:3 4715:d 4704:4 4700:d 4689:1 4684:0 4679:0 4674:0 4667:0 4662:1 4657:0 4652:0 4645:0 4640:0 4635:1 4630:0 4624:[ 4619:= 4616:) 4613:t 4610:( 4600:x 4570:. 4562:4 4558:d 4554:+ 4551:s 4546:3 4542:d 4538:+ 4533:2 4529:s 4523:2 4519:d 4515:+ 4510:3 4506:s 4500:1 4496:d 4492:+ 4487:4 4483:s 4475:4 4471:n 4467:+ 4464:s 4459:3 4455:n 4451:+ 4446:2 4442:s 4436:2 4432:n 4428:+ 4423:3 4419:s 4413:1 4409:n 4402:= 4399:) 4396:s 4393:( 4388:G 4333:p 4327:q 4307:) 4304:s 4301:( 4297:G 4284:. 4271:D 4267:+ 4263:B 4257:1 4250:) 4245:A 4237:I 4233:s 4230:( 4226:C 4222:= 4219:) 4216:s 4213:( 4209:G 4182:) 4179:s 4176:( 4172:U 4168:) 4165:s 4162:( 4158:G 4154:= 4151:) 4148:s 4145:( 4141:Y 4109:) 4106:s 4103:( 4100:U 4096:/ 4092:) 4089:s 4086:( 4083:Y 4080:= 4077:) 4074:s 4071:( 4068:G 4039:0 4035:= 4032:) 4029:0 4026:( 4022:x 3998:. 3995:) 3992:s 3989:( 3985:U 3980:D 3976:+ 3973:) 3970:) 3967:s 3964:( 3960:U 3955:B 3949:1 3942:) 3937:A 3929:I 3925:s 3922:( 3919:+ 3916:) 3913:0 3910:( 3906:x 3900:1 3893:) 3888:A 3880:I 3876:s 3873:( 3870:( 3866:C 3862:= 3859:) 3856:s 3853:( 3849:Y 3822:, 3819:) 3816:s 3813:( 3809:U 3804:D 3800:+ 3797:) 3794:s 3791:( 3787:X 3782:C 3778:= 3775:) 3772:s 3769:( 3765:Y 3741:) 3738:s 3735:( 3731:X 3707:. 3704:) 3701:s 3698:( 3694:U 3689:B 3683:1 3676:) 3671:A 3663:I 3659:s 3656:( 3653:+ 3650:) 3647:0 3644:( 3640:x 3634:1 3627:) 3622:A 3614:I 3610:s 3607:( 3604:= 3601:) 3598:s 3595:( 3591:X 3564:) 3561:s 3558:( 3554:U 3549:B 3545:+ 3542:) 3539:0 3536:( 3532:x 3528:= 3525:) 3522:s 3519:( 3515:X 3511:) 3507:A 3499:I 3495:s 3492:( 3469:) 3466:s 3463:( 3459:X 3435:. 3432:) 3429:s 3426:( 3422:U 3417:B 3413:+ 3410:) 3407:s 3404:( 3400:X 3395:A 3391:= 3388:) 3385:0 3382:( 3378:x 3371:) 3368:s 3365:( 3361:X 3357:s 3331:) 3328:t 3325:( 3321:u 3316:B 3312:+ 3309:) 3306:t 3303:( 3299:x 3294:A 3290:= 3287:) 3284:t 3281:( 3271:x 3225:. 3222:n 3219:= 3214:] 3206:1 3200:n 3195:A 3189:C 3173:A 3168:C 3159:C 3152:[ 3109:n 3088:, 3085:n 3082:= 3077:] 3070:B 3064:1 3058:n 3053:A 3040:B 3034:2 3029:A 3021:B 3016:A 3009:B 3002:[ 2931:) 2928:s 2925:( 2920:G 2868:. 2864:| 2859:A 2851:I 2847:s 2843:| 2839:= 2836:) 2833:s 2830:( 2803:A 2795:I 2791:s 2760:. 2754:) 2749:4 2745:p 2738:s 2735:( 2732:) 2727:3 2723:p 2716:s 2713:( 2710:) 2705:2 2701:p 2694:s 2691:( 2688:) 2683:1 2679:p 2672:s 2669:( 2664:) 2659:3 2655:z 2648:s 2645:( 2642:) 2637:2 2633:z 2626:s 2623:( 2620:) 2615:1 2611:z 2604:s 2601:( 2595:k 2592:= 2589:) 2586:s 2583:( 2578:G 2548:A 2509:) 2506:z 2503:( 2499:U 2494:D 2490:+ 2487:) 2484:z 2481:( 2477:X 2472:C 2468:= 2465:) 2462:z 2459:( 2455:Y 2434:) 2431:z 2428:( 2424:U 2419:B 2415:+ 2412:) 2409:z 2406:( 2402:X 2397:A 2393:= 2390:) 2387:0 2384:( 2380:x 2376:z 2370:) 2367:z 2364:( 2360:X 2356:z 2325:) 2322:s 2319:( 2315:U 2310:D 2306:+ 2303:) 2300:s 2297:( 2293:X 2288:C 2284:= 2281:) 2278:s 2275:( 2271:Y 2250:) 2247:s 2244:( 2240:U 2235:B 2231:+ 2228:) 2225:s 2222:( 2218:X 2213:A 2209:= 2206:) 2203:0 2200:( 2196:x 2189:) 2186:s 2183:( 2179:X 2175:s 2144:) 2141:k 2138:( 2134:u 2130:) 2127:k 2124:( 2120:D 2116:+ 2113:) 2110:k 2107:( 2103:x 2099:) 2096:k 2093:( 2089:C 2085:= 2082:) 2079:k 2076:( 2072:y 2051:) 2048:k 2045:( 2041:u 2037:) 2034:k 2031:( 2027:B 2023:+ 2020:) 2017:k 2014:( 2010:x 2006:) 2003:k 2000:( 1996:A 1992:= 1989:) 1986:1 1983:+ 1980:k 1977:( 1973:x 1946:) 1943:k 1940:( 1936:u 1931:D 1927:+ 1924:) 1921:k 1918:( 1914:x 1909:C 1905:= 1902:) 1899:k 1896:( 1892:y 1871:) 1868:k 1865:( 1861:u 1856:B 1852:+ 1849:) 1846:k 1843:( 1839:x 1834:A 1830:= 1827:) 1824:1 1821:+ 1818:k 1815:( 1811:x 1784:) 1781:t 1778:( 1774:u 1770:) 1767:t 1764:( 1760:D 1756:+ 1753:) 1750:t 1747:( 1743:x 1739:) 1736:t 1733:( 1729:C 1725:= 1722:) 1719:t 1716:( 1712:y 1691:) 1688:t 1685:( 1681:u 1677:) 1674:t 1671:( 1667:B 1663:+ 1660:) 1657:t 1654:( 1650:x 1646:) 1643:t 1640:( 1636:A 1632:= 1629:) 1626:t 1623:( 1613:x 1583:) 1580:t 1577:( 1573:u 1568:D 1564:+ 1561:) 1558:t 1555:( 1551:x 1546:C 1542:= 1539:) 1536:t 1533:( 1529:y 1508:) 1505:t 1502:( 1498:u 1493:B 1489:+ 1486:) 1483:t 1480:( 1476:x 1471:A 1467:= 1464:) 1461:t 1458:( 1448:x 1400:t 1380:k 1359:Z 1352:t 1331:R 1324:t 1304:t 1288:. 1276:) 1273:t 1270:( 1266:x 1259:t 1256:d 1252:d 1244:) 1241:t 1238:( 1228:x 1214:, 1202:p 1196:q 1193:= 1190:] 1187:) 1181:( 1177:D 1173:[ 1147:) 1141:( 1137:D 1116:) 1110:( 1106:D 1095:, 1083:n 1077:q 1074:= 1071:] 1068:) 1062:( 1058:C 1054:[ 1028:) 1022:( 1018:C 1007:, 995:p 989:n 986:= 983:] 980:) 974:( 970:B 966:[ 940:) 934:( 930:B 919:, 907:n 901:n 898:= 895:] 892:) 886:( 882:A 878:[ 852:) 846:( 842:A 831:; 817:p 812:R 804:) 801:t 798:( 794:u 773:) 767:( 763:u 752:; 738:q 733:R 725:) 722:t 719:( 715:y 694:) 688:( 684:y 673:; 659:n 654:R 646:) 643:t 640:( 636:x 615:) 609:( 605:x 578:) 575:t 572:( 568:u 564:) 561:t 558:( 554:D 550:+ 547:) 544:t 541:( 537:x 533:) 530:t 527:( 523:C 519:= 516:) 513:t 510:( 506:y 484:) 481:t 478:( 474:u 470:) 467:t 464:( 460:B 456:+ 453:) 450:t 447:( 443:x 439:) 436:t 433:( 429:A 425:= 422:) 419:t 416:( 406:x 379:n 359:q 339:p 295:n 240:p 234:q 214:q 194:p 83:) 77:( 72:) 68:( 54:. 20:)

Index

State space representation
references
inline citations
improve
introducing
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quantum state space
configuration space (physics)
control engineering
system identification
mathematical model
variables
differential equations
difference equations
phase space
geometric space
vector
dynamical system
algebraic equations
matrix
system theory
Kronecker vector-matrix structures
time-domain
Laplace transforms
frequency domain
econometrics
time series
Kalman Filter
state variables
capacitors

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