Name
Abstract | ||
|---|---|---|
Most models of Bidirectional associative memories intend to achieve that all trained pattern correspond to stable states; however, this has not been possible. Also, none of the former models has been able to recall all the trained patterns. In this work we introduce a new model of bidirectional associative memory which is not iterative and has no stability problems. It is based on the Alpha-Beta associative memories. This model allows perfect recall of all trained patterns, with no ambiguity and no conditions. Applications of Alpha-Beta Bidirectional Associative Memories as fingerprint recognition and translator are presented. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.5019/j.ijcir.2007.94 | COMPUTACION Y SISTEMAS |
Keywords | Field | DocType |
Bidirectional Associative Memories, Alpha-Beta Associative Memories, correct recall | Associative property,Bidirectional associative memory,Stable states,Fingerprint recognition,Psychology,Artificial intelligence,Recall,Ambiguity | Journal |
Volume | Issue | ISSN |
10 | 1 | 1405-5546 |
Citations | PageRank | References |
0 | 0.34 | 7 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| María Elena Acevedo-Mosqueda | 1 | 20 | 2.63 |
| Cornelio Yáñez-Márquez | 2 | 153 | 26.34 |
| Itzamá López-Yáñez | 3 | 78 | 11.76 |