Neuro-Fuzzy Methods for Modeling and Identification-Reference-Cited by-同舟云学术

Neuro-Fuzzy Methods for Modeling and Identification

Published:2003 Issue: Volume: Page:161-186
ISSN:1434-9922
Container-title:Recent Advances in Intelligent Paradigms and Applications
language:
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Author:

Babuška Robert

Publisher

Physica-Verlag HD

Link

http://link.springer.com/content/pdf/10.1007/978-3-7908-1770-6_8.pdf

Reference14 articles.

1. P.J. Werbos. Beyond regression: new tools for prediction and analysis in the behavior sciences. PhD Thesis, Harvard University, Committee on Applied Mathematics, 1974.

2. D. E. Rumelhart, G. E. Hinton, and R. J. Williams. Learning representations by back-propagating errors. Nature, 323: 533–536, 1986.

3. J.-S.R. Jang and C.-T. Sun. Functional equivalence between radial basis function networks and fuzzy inference systems. IEEE Transactions on Neural Networks,4(1):156159, January 1993.

4. M. Brown and C. Harris. Neurofuzzy Adaptive Modelling and Control. Prentice Hall, New York, 1994.

5. J.-S.R. Jang. ANFIS: Adaptive-network-based fuzzy inference systems. IEEE Transactions on Systems, Man & Cybernetics, 23 (3): 665–685, May 1993.

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