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Subspace Identification for Linear Systems
Overschee, Peter Van; Moor, B. L. de
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Description for Subspace Identification for Linear Systems
Paperback. Num Pages: 272 pages, biography. BIC Classification: GPFC; TGB; THR; TTBM. Category: (P) Professional & Vocational. Dimension: 235 x 158 x 15. Weight in Grams: 392.
Subspace Identification for Linear Systems focuses on the theory, implementation and applications of subspace identification algorithms for linear time-invariant finite- dimensional dynamical systems. These algorithms allow for a fast, straightforward and accurate determination of linear multivariable models from measured input-output data.
The theory of subspace identification algorithms is presented in detail. Several chapters are devoted to deterministic, stochastic and combined deterministic-stochastic subspace identification algorithms. For each case, the geometric properties are stated in a main 'subspace' Theorem. Relations to existing algorithms and literature are explored, as are the ... Read more
Subspace Identification for Linear Systems focuses on the theory, implementation and applications of subspace identification algorithms for linear time-invariant finite- dimensional dynamical systems. These algorithms allow for a fast, straightforward and accurate determination of linear multivariable models from measured input-output data.
The theory of subspace identification algorithms is presented in detail. Several chapters are devoted to deterministic, stochastic and combined deterministic-stochastic subspace identification algorithms. For each case, the geometric properties are stated in a main 'subspace' Theorem. Relations to existing algorithms and literature are explored, as are the ... Read more
Product Details
Format
Paperback
Publication date
2011
Publisher
Springer-Verlag New York Inc. United States
Number of pages
272
Condition
New
Number of Pages
272
Place of Publication
New York, NY, United States
ISBN
9781461380610
SKU
V9781461380610
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15
Reviews for Subspace Identification for Linear Systems
`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) ... Read more