System Identification: Theory for the UserPrentice-Hall, 1987 - 519 sidor This book is a description of the theory, methodology and practice of System Identification - the science of building mathematical models of dynamic systems by observing input/output data. |
Innehåll
INTRODUCTION | 1 |
systems and models | 13 |
SIMULATION PREDICTION AND CONTROL | 51 |
Upphovsrätt | |
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algorithm analogous applied arg min assume assumption Åström asymptotic b₁ basic black-box Bode plot Chapter choice computed Consider convergence correlation corresponding covariance matrix Cramér-Rao bound criterion data set defined denotes described design variables discussed distribution disturbances dynamics eo(t equation example expression Figure filter formal frequency Gaussian given gives Go(e Hence independent input input-output Kalman filter Lemma likelihood function linear regression Ljung measured minimization model order model set model structure multivariable noise model nonlinear norm obtained optimal output error parameter estimation periodogram polynomials prediction errors predictor prefilter problem properties quadratic random variables recursive regressors result sampling interval scalar Section sequence signal simulation Söderström spectrum state-space model stochastic process Suppose system identification techniques Theorem transfer function true system typically variance vector vo(t white noise θο λο Φω(ω ユー
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Stochastic Approximation and Recursive Algorithms and Applications Harold Kushner,G. George Yin Ingen förhandsgranskning - 2003 |