| Resumen |
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. |
