Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10360637 | Pattern Recognition | 2005 | 13 Pages |
Abstract
In this paper, we present a multi-objective evolutionary algorithm which is able to determine the optimal size of recurrent neural networks in any particular application. This is specially analyzed in the case of grammatical inference: in particular, we study how to establish the optimal size of a recurrent neural network in order to learn positive and negative examples in a certain language, and how to determine the corresponding automaton using a self-organizing map once the training has been completed.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Vision and Pattern Recognition
Authors
M. Delgado, M.C. Pegalajar,