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Filtering and System Identification by Vincent Verdult, Michel Verhaegen

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9

Subspace model identification

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After studying this chapter you will be able to

•  derive the data equation that relates block Hankel matrices constructed from input–output data;

•  exploit the special structure of the data equation for impulse input signals to identify a state-space model via subspace methods;

•  use subspace identification for general input signals;

•  use instrumental variables in subspace identification to deal with process and measurement noise;

•  derive subspace identification schemes for various noise models;

•  use the RQ factorization for a computationally efficient implementation of subspace identification schemes; ...

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