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Alle Exemplare der Ausgabe mit dieser ISBN anzeigen:From the reviews:
"The book is devoted to subspace methods used for system identification. ... The book contains also some tutorial problems with solutions and MATLAB programs, which demonstrate various aspects of the methods propounded to introductory and research material. Therefore it may be a valuable reference for researches as well, a very useful text for tutors and graduate students involved with courses in control and signal processing. The book is clearly written and well organized." (Ryszard Gessing, Zentralblatt MATH, Vol. 1118 (20), 2007)
"Subspace identification methods have become a major tool in system identification during the last decades. ... The book is written in a systematic way and generally easy to follow. The ideas are presented in a systematic and coherent manner. ... the monograph is suited for researchers, practitioners and graduate students, in particular from an (systems) engineering community. It provides an excellent reference book for realization theory and linear systems." (Wolfgang Scherrer, International Journal of Robust and Nonlinear Control, Vol. 18, 2008)
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.
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Buchbeschreibung Kartoniert / Broschiert. Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. The introductory material combined with novel research results and proofs will make this an all-in-one reference of subspace identification methods for control and signal processing researchersDevelops new results in stochastic realization theory . Bestandsnummer des Verkäufers 4289033
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Buchbeschreibung Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 408 pp. Englisch. Bestandsnummer des Verkäufers 9781849969888
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Buchbeschreibung Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. Bestandsnummer des Verkäufers 9781849969888
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