ON the influence of parameter theta- on performance of RBF neural networks trained with the dynamic decay adjustment algorithm

The dynamic decay adjustment (DDA) algorithm is a fast constructive algorithm for training RBF neural networks (RBFNs) and probabilistic neural networks (PNNs). The algorithm has two parameters, namely, theta(+) and theta(-). The papers which introduced DDA argued that those parameters would not hea...

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Bibliographic Details

Published in:	International journal of neural systems Vol. 16; no. 4; p. 271
Main Authors:	Oliveira, Adriano L I, Medeiros, Ericles A, Rocha, Thyago A B V, Bezerra, Miguel E R, Veras, Ronaldo C
Format:	Journal Article
Language:	English
Published:	Singapore 01.08.2006
Subjects:	Algorithms Artificial Intelligence Models, Statistical Neural Networks (Computer) Nonlinear Dynamics Time Factors
ISSN:	0129-0657
Online Access:	Get more information
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