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  $264.95
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Nonlinear Modeling: Advanced Black-Box Techniquesby Johan A. K. Suykens
Synopses & ReviewsBook News Annotation:This collection of eight contributions presents advanced black-box
techniques for nonlinear modeling. The methods discussed include
neural nets and related model structures for nonlinear system
identification, enhanced multi-stream Kalman filter training for
recurrent networks, the support vector method of function estimation,
parametric density estimation for the classification of acoustic
feature vectors in speech recognition, wavelet based modeling of
nonlinear systems, nonlinear identification based on fuzzy models,
statistical learning in control and matrix theory, and nonlinear
time- series analysis. The volume concludes with the results of a
time- series prediction competition held at a July 1998 workshop in
Belgium.
Annotation c. by Book News, Inc., Portland, OR (booknews.com) Synopsis:Nonlinear Modeling: Advanced Black-Box Techniques discusses methods on Neural nets and related model structures for nonlinear system identification; Enhanced multi-stream Kalman filter training for recurrent networks; The support vector method of function estimation; Parametric density estimation for the classification of acoustic feature vectors in speech recognition; Wavelet-based modeling of nonlinear systems; Nonlinear identification based on fuzzy models; Statistical learning in control and matrix theory; Nonlinear time-series analysis. It also contains the results of the K.U. Leuven time series prediction competition, held within the framework of an international workshop at the K.U. Leuven, Belgium in July 1998. What Our Readers Are SayingBe the first to add a comment for a chance to win!Product Details
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