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Subspace Methods for System Identification (Communications and Control Engineering),Used
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An indepth introduction to subspace methods for system identification in discretetime linear systems thoroughly augmented with advanced and novel results, this text is structured into three parts.Part I deals with the mathematical preliminaries: numerical linear algebra; system theory; stochastic processes; and Kalman filtering. Part II explains realization theory as applied to subspace identification. Stochastic realization results based on spectral factorization and Riccati equations, and on canonical correlation analysis for stationary processes are included. Part III demonstrates the closedloop application of subspace identification methods.Subspace Methods for System Identification is an excellent reference for researchers and a useful text for tutors and graduate students involved in control and signal processing courses. It can be used for selfstudy and will be of interest to applied scientists or engineers wishing to use advanced methods in modeling and identification of complex systems.
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