Centro de Investigación en Computación, Instituto Politécnico Nacional, Laboratorio de Inteligencia Artificial v. Juan de Dios Bátiz s/n, México, D. F., 07738, México
* E-mail: eacevedo@ipn.mx
** E-mail: cyanez@cic.ipn.mx
*** E-mail: ilopezb05@sagitario.cic.ipn.mx
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. An example of fingerprint recognition is presented.
Bidirectional associative memories, Alpha-Beta associative memories, perfect recall
