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Author:   Peter van Overschee ,  B.L. de Moor
Publisher:   Springer-Verlag New York Inc.
Imprint:   Springer-Verlag New York Inc.
Edition:   Softcover reprint of the original 1st ed. 1996
Dimensions:   Width: 15.50cm , Height: 1.40cm , Length: 23.50cm
Weight:   0.417kg
ISBN:  

9781461380610

ISBN 10:   1461380618
Pages:   272
Publication Date:   08 October 2011
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand  
We will order this item for you from a manufactured on demand supplier.

Table of Contents

1 Introduction, Motivation and Geometric Tools.- 1.1 Models of systems and system identification.- 1.2 A new generation of system identification algorithms.- 1.3 Overview.- 1.4 Geometric tools.- 1.5 Conclusions.- 2 Deterministic Identification.- 2.1 Deterministic systems.- 2.2 Geometric properties of deterministic systems.- 2.3 Relation to other algorithms.- 2.4 Computing the system matrices.- 2.5 Conclusions.- 3 Stochastic Identification.- 3.1 Stochastic systems.- 3.2 Geometric properties of stochastic systems.- 3.3 Relation to other algorithms.- 3.4 Computing the system matrices.- 3.5 Conclusions.- 4 Combined Deterministic-Stochastic Identification.- 4.1 Combined systems.- 4.2 Geometric properties of combined systems.- 4.3 Relation to other algorithms.- 4.4 Computing the system matrices.- 4.5 Connections to the previous Chapters.- 4.6 Conclusions.- 5 State Space Bases and Model Reduction.- 5.1 Introduction.- 5.2 Notation.- 5.3 Frequency weighted balancing.- 5.4 Subspace identification and frequency weighted balancing.- 5.5 Consequences for reduced order identification.- 5.6 Example.- 5.7 Conclusions.- 6 Implementation and Applications.- 6.1 Numerical Implementation.- 6.2 Interactive System Identification.- 6.3 An Application of ISID.- 6.4 Practical examples in Matlab.- 6.5 Conclusions.- 7 Conclusions and Open Problems.- 7.1 Conclusions.- 7.2 Open problems.- A Proofs.- A.1 Proof of formula (2.16).- A.2 Proof of Theorem 6.- A.3 Note on the special form of the Kalman filter.- A.4 Proof of Theorem 8.- A.5 Proof of Theorem 9.- A.6 Proof of Theorem 11.- A.7 Proof of Theorem 12.- A.8 Proof of Lemma 2.- A.9 Proof of Theorem 13.- A.10 Proof of Corollary 2 and 3.- A.11 Proof of Theorem 14.- B Matlab Functions.- B.1 Getting started.- B.2 Matlab Reference.- B.2.1 Directory: ‘subfun’.- B.2.2 Directory: ‘applic’.- B.2.3 Directory: ‘examples’.- B.2.4 Directory: ‘figures’.- C Notation.- References.

Reviews

The book is definitely a must for academics and engineers who are interested in modern system identification techniques. Since the main algorithms are supplied on a disk accompanying the book, it is very easy to get started using the proposed algorithms.' T. McKelvey, International Journal of Adaptive Control and Signal Processing, 12:6, (1998)

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