@inproceedings{9693f275284f44939cc2ec35ebc8aa81,
title = "A new bi-directional associative memory",
abstract = "Hebbian hetero-associative learning is inherently asymmetric. Storing a forward association from pattern A to pattern B enables the recalling of pattern B given pattern A. This, in general, does not allow the recalling of pattern A given pattern B. The forward association between A and B will tend to be stronger than the backward association between B and A. In this paper it is described how the dynamical associative model proposed in [10] can be extended to create a bi-directional associative memory where forward association between A and B is equal to backward association between B and A. This implies that storing a forward association, from pattern A to pattern B, would enable the recalling of pattern B given pattern A and the recalling of pattern A given pattern B. We give some formal results that support the functioning of the proposal, and provide some examples were the proposal finds application.",
author = "V{\'a}zquez, {Roberto A.} and Humberto Sossa and Garro, {Beatriz A.}",
year = "2006",
doi = "10.1007/11925231_35",
language = "Ingl{\'e}s",
isbn = "3540490264",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "367--380",
booktitle = "MICAI 2006",
address = "Alemania",
note = "5th Mexican International Conference on Artificial Intelligence, MICAI 2006: Advances in Artificial Intelligence ; Conference date: 13-11-2006 Through 17-11-2006",
}