Artigo Revisado por pares

Resilient back propagation learning algorithm for recurrent fuzzy neural networks

2004; Institution of Engineering and Technology; Volume: 40; Issue: 1 Linguagem: Inglês

10.1049/el

ISSN

1350-911X

Autores

Paris Mastorocostas,

Tópico(s)

Fuzzy Logic and Control Systems

Resumo

An efficient training method for recurrent fuzzy neural networks is proposed. The method modifies the RPROP algorithm, originally developed for static neural networks, in order to be applied to dynamic systems. A comparative analysis with the standard back propagation through time is given, indicating the effectiveness of the proposed algorithm.

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