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Subspace Identification for Linear Systems : Theory — Implementation — Applications by Peter Van Overschee, Bart De Moor (auth.) is a nonfiction available to read on EtoBox.

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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 Interconnections Between Different Subspace Algorithms. The Subspace Identification Theory Is Linked To The Theory Of Frequency Weighted Model Reduction, Which Leads To New Interpretations And Insights. The Implementation Of Subspace Identification Algorithms Is Discussed In Terms Of The Robust And Computationally Efficient Rq And Singular Value Decompositions, Which Are Well-established Algorithms From Numerical Linear Algebra. The Algorithms Are Implemented In Combination With A Whole Set Of

Who reads Subspace Identification for Linear Systems : Theory — Implementation — Applications?

Author

Peter Van Overschee, Bart De Moor (auth.)

Publisher

Springer US

Published

1996

Language

EN

ISBN

9780792397175

Category

nonfiction

Subjects

Science, Engineering, Mathematics