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Titolo:
Searching for a solution to the automatic RBF network design problem
Autore:
Sanchez, VD;
Indirizzi:
Adv Computat Intelligent Syst, Pasadena, CA 91116 USA Adv Computat Intelligent Syst Pasadena CA USA 91116 asadena, CA 91116 USA
Titolo Testata:
NEUROCOMPUTING
, volume: 42, anno: 2002,
pagine: 147 - 170
SICI:
0925-2312(200201)42:<147:SFASTT>2.0.ZU;2-1
Fonte:
ISI
Lingua:
ENG
Soggetto:
RADIAL BASIS FUNCTIONS; GENETIC EVOLUTION; NEURAL NETWORKS; APPROXIMATION; ALGORITHM;
Keywords:
clustering; computational learning theory; evolutionary computation; genetic algorithms; neural networks; pattern recognition; RBF networks; regression; statistical learning theory;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Engineering, Computing & Technology
Citazioni:
64
Recensione:
Indirizzi per estratti:
Indirizzo: Sanchez, VD Adv Computat Intelligent Syst, Pasadena, CA 91116 USA Adv Computat Intelligent Syst Pasadena CA USA 91116 91116 USA
Citazione:
V.D. Sanchez, "Searching for a solution to the automatic RBF network design problem", NEUROCOMPUT, 42, 2002, pp. 147-170

Abstract

While amazing applications have been demonstrated in different science andengineering fields using neural networks and evolutionary approaches, one of the key elements of their further acceptance and proliferation is the study and provision of procedures for the automatic design of neural architectures and associated learning methods, i.e., in general, the study of the systematic and automatic design of artificial brains. In this contribution, connections between conventional techniques of pattern recognition, evolutionary approaches, and newer results from computational and statistical learning theory are brought together in the context of the automatic design of RBF regression networks. (C) 2002 Elsevier Science B.V. All rights reserved.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 04/07/20 alle ore 18:30:39