Overview
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Table of contents (9 chapters)
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Front Matter
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Back Matter
Keywords
About this book
- 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.
Editors and Affiliations
Bibliographic Information
Book Title: Nonlinear Modeling
Book Subtitle: Advanced Black-Box Techniques
Editors: Johan A. K. Suykens, Joos Vandewalle
DOI: https://doi.org/10.1007/978-1-4615-5703-6
Publisher: Springer New York, NY
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eBook Packages: Springer Book Archive
Copyright Information: Springer Science+Business Media Dordrecht 1998
Hardcover ISBN: 978-0-7923-8195-2Published: 30 June 1998
Softcover ISBN: 978-1-4613-7611-8Published: 05 November 2012
eBook ISBN: 978-1-4615-5703-6Published: 06 December 2012
Edition Number: 1
Number of Pages: XVII, 256
Topics: Circuits and Systems, Complex Systems, Systems Theory, Control, Signal, Image and Speech Processing, Electrical Engineering, Statistical Physics and Dynamical Systems