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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 copyrighted by Book News, Inc., Portland, OR.
This collection of eight contributions presents advanced black-box techniques for nonlinear modeling. The methods discussed include neural nets and related mode
Adaptive Learning Methods for Nonlinear System Modeling presents some of the recent advances on adaptive algorithms and machine learning methods designed for no
This book presents theories of deformable elastic strings and rods and their application to broad classes of problems. Readers will gain insights into the formu
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There are many books on the use of numerical methods for solving engineering problems and for modeling of engineering artifacts. In addition there are many styl