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Combined Parametric-Nonparametric Identification of Block-Oriented Systems (Paperback, 2014 ed.)
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Combined Parametric-Nonparametric Identification of Block-Oriented Systems (Paperback, 2014 ed.)
Series: Lecture Notes in Control and Information Sciences, 454
Expected to ship within 10 - 15 working days
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This book considers a problem of block-oriented nonlinear dynamic
system identification in the presence of random disturbances. This
class of systems includes various interconnections of linear
dynamic blocks and static nonlinear elements, e.g., Hammerstein
system, Wiener system, Wiener-Hammerstein ("sandwich") system and
additive NARMAX systems with feedback. Interconnecting signals are
not accessible for measurement. The combined
parametric-nonparametric algorithms, proposed in the book, can be
selected dependently on the prior knowledge of the system and
signals. Most of them are based on the decomposition of the complex
system identification task into simpler local sub-problems by using
non-parametric (kernel or orthogonal) regression estimation. In the
parametric stage, the generalized least squares or the instrumental
variables technique is commonly applied to cope with correlated
excitations. Limit properties of the algorithms have been shown
analytically and illustrated in simple experiments.
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