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Abstract: A major drawback of the truncated Volterra series or "Volterra filter" for system identification is the large number of parameters required by the standard filter structure. The corresponding estimation problem requires the solution of a large system of simultaneous linear equations. Two methods for simplifying the estimation problem are discussed in this paper. First, a Kronecker product structure for the Volterra filter is reviewed. In this approach the inverse of the large correlation matrix ... (Update)
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...Wisconsin, 1415 Johnson Drive, Madison, WI 53706. an N th order Volterra filter, then the output is a linear combination of the random variables [11] f m Y i=1 X n i i : m X i=1 n i N; n i 2 f0; 1; Ng g: 1) There are exactly r m = m N m ) random variables in the...
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BibTeX entry: (Update)
@misc{ nowak-efficient,
author = "Models Robert Nowak",
title = "Efficient Methods for Identification of Volterra Filter",
url = "citeseer.ist.psu.edu/nowak94efficient.html" }
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