Subspace Methods for System Identification



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Éditeur :

Springer


Collection :

Communications and Control Engineering

Paru le : 2005-10-11



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Description
An in-depth introduction to subspace methods for system identification in discrete-time 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 closed-loop 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 self-study and will be of interest to applied scientists or engineers wishing to use advanced methods in modeling and identification of complex systems.
Pages
392 pages
Collection
Communications and Control Engineering
Parution
2005-10-11
Marque
Springer
EAN papier
9781852339814
EAN PDF
9781846281587

Informations sur l'ebook
Nombre pages copiables
3
Nombre pages imprimables
39
Taille du fichier
5878 Ko
Prix
147,69 €