Buch, Englisch, 392 Seiten, Previously published in hardcover, Format (B × H): 155 mm x 235 mm, Gewicht: 616 g
Buch, Englisch, 392 Seiten, Previously published in hardcover, Format (B × H): 155 mm x 235 mm, Gewicht: 616 g
Reihe: Communications and Control Engineering
ISBN: 978-1-84996-988-8
Verlag: Springer
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.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik EDV | Informatik Informatik Bildsignalverarbeitung
- Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle
- Technische Wissenschaften Technik Allgemein Mess- und Automatisierungstechnik
- Technische Wissenschaften Elektronik | Nachrichtentechnik Nachrichten- und Kommunikationstechnik Funktechnik
- Technische Wissenschaften Verfahrenstechnik | Chemieingenieurwesen | Biotechnologie Verfahrenstechnik, Chemieingenieurwesen
- Technische Wissenschaften Sonstige Technologien | Angewandte Technik Signalverarbeitung, Bildverarbeitung, Scanning
Weitere Infos & Material
Preliminaries.- Linear Algebra and Preliminaries.- Discrete-Time Linear Systems.- Stochastic Processes.- Kalman Filter.- Realization Theory.- Realization of Deterministic Systems.- Stochastic Realization Theory (1).- Stochastic Realization Theory (2).- Subspace Identification.- Subspace Identification (1) — ORT.- Subspace Identification (2) — CCA.- Identification of Closed-loop System.