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System ID

System Identification for Control Using MATLAB  
By Shuichi Adachi, ISBN 4-254-11073-1 Written in Japanese and designed for the beginner in the area of systemidentification, this book focuses on the basic theory of system identificationfor control systems. Numerous examples using MATLAB and the System IdentificationToolbox are presented to help the reader understand the fundamental conceptsof system identification.
Submitted: Dec 24, 2003
Multivariable System Identification: for Process Control  
By Yucai Zhu. Written for students and practicing engineers, this book discusses industrial solutions to process identification based upon scientific theory. Topics covered include various identification methods, including linear and block-oriented nonlinear models; detailed project procedures for multivariable process identification control; and identification test design and model validation. MATLAB and the System Identification Toolbox are used to solve numerous example problems throughout the book.
Submitted: Feb 20, 2004
Modeling of Dynamic Systems  
By Lennart Ljung & Torkel Glad. The material presented in this book is appropriate for engineering students and practicing engineers. It discusses the process of transferring physical facts, intuitive insights, and information in measured signals into useful mathematical models. It also shows how to use those models in simulation applications. The book covers many of the theories and methods contained in the System Identification Toolbox, a MATLAB application toolbox developed by Lennart Ljung.
Submitted: Feb 20, 2004
System Identification: Theory for the User, 2e  
By Lennart Ljung, ISBN 0-13-656695-2 This textbook presents the theoretical foundation for the System IdentificationToolbox. It gives the reader an understanding of available system identificationmethods and their rationales, properties, and uses. This second editionintroduces subspace methods, methods that utilize frequency-domain data,and general, nonlinear, black box methods including neural networks andneuro-fuzzy modeling. The book contains many new computer-based examples,which utilize the System Identification Toolbox, a MATLAB applicationtoolbox developed by Lennart Ljung. The toolbox may be purchased fromThe MathWorks.
Submitted: Dec 24, 2003
Subspace Identification for Linear Systems: Theory, Implementation Applications  
By Peter van Overschee & Bart De Moor, ISBN 0-7923-9717-7 This book focuses on the theory, implementation, and applications of subspaceidentification algorithms for linear time-invariant finite-dimensionaldynamical systems. The theory is presented in detail and several chaptersare devoted to deterministic, stochastic, and combined deterministic-stochasticsubspace identification algorithms. The application of MATLAB to ten practicalproblems illustrates the use of subspace identification algorithms inindustry.
Submitted: Dec 24, 2003
Adaptive Blind Signal and Image Processing: Learning Algorithms and Applications  
By Andrzej Cichocki & Shun-ici Amari. Written for engineers and researchers in various fields, this book covers both the theory and application of adaptive blind signal processing techniques and algorithms. Practical techniques for adaptive blind signal and image separation, extraction, decomposition, and filtering of multi-variable signals and data are discussed.
Submitted: Feb 20, 2004
Identyfikacja obiektow i sygnalow: Teoria i praktyka dla uzytkowników MATLAB  
By Aleksandra Zimmer. Written in Polish, this book introduces the reader to the fundamentals of system identification. Standard parametric models are presented with state-space models and spectral methods for stationary and nonstationary processes. Kalman filters for state estimation are also discussed. Numerous application examples are presented with MATLAB and the System Identification Toolbox.
Submitted: Feb 20, 2004
Modelování A Identifikace Systému  
By Petr Noskievic, ISBN 80-7225-030-2
Submitted: Dec 24, 2003

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