| Título |
Automatic Design of Artificial Neural Networks and Associative Memories for Pattern Classification and Pattern Restoration |
| Tipo |
Congreso |
| Sub-tipo |
SCOPUS |
| Descripción |
Lecture Notes in Computer Science; 4th Mexican Conference on Pattern Recognition |
| Resumen |
In this note we present our most recent advances in the automatic design of artificial neural networks (ANNs) and associative memories (AMs) for pattern classification and pattern recall. Particle Swarm Optimization (PSO), Differential Evolution (DE), and Artificial Bee Colony (ABC) algorithms are used for ANNs; Genetic Programming is adopted for AMs. The derived ANNs and AMs are tested with several examples of well-known databases. As we will show, results are very promising. |
| Observaciones |
Pattern Recognition, MCPR 2012; (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Code 91407 |
| Lugar |
Huatulco |
| País |
Mexico |
| No. de páginas |
23-34 |
| Vol. / Cap. |
7329 |
| Inicio |
2012-06-27 |
| Fin |
2012-06-30 |
| ISBN/ISSN |
978-3-642-31148-2 |
