| Título |
Transforming fundamental set of patterns to a canonical form to improve pattern recall |
| Tipo |
Revista |
| Sub-tipo |
JCR |
| Descripción |
Lecture Notes in Artificial Intelligence; 9th Ibero-American Conference on AI: Advances in Artificial Intelligence |
| Resumen |
Most results (lemmas and theorems) providing conditions under which associative memories are able to perfectly recall patterns of a fundamental set are very restrictive in most practical applications. In this note we describe a simple but effective procedure to transform a fundamental set of patterns (FSP) to a canonical form that fulfils the propositions. This way pattern recall is strongly improved. We provide numerical and real examples to reinforce the proposal. |
| Observaciones |
Advances in Artificial Intelligence – IBERAMIA 2004; Code 65317 |
| Lugar |
Puebla |
| País |
Mexico |
| No. de páginas |
687-696 |
| Vol. / Cap. |
3315 |
| Inicio |
2004-11-22 |
| Fin |
2004-11-26 |
| ISBN/ISSN |
978-3-540-23806-5 |
