Bidirectional associative memories
IEEE Transactions on Systems, Man and Cybernetics
Morphological bidirectional associative memories
Neural Networks
IEEE Transactions on Computers
A new strategy for designing bidirectional associative memories
ISNN'05 Proceedings of the Second international conference on Advances in Neural Networks - Volume Part I
Morphological associative memories
IEEE Transactions on Neural Networks
A feedforward bidirectional associative memory
IEEE Transactions on Neural Networks
Encoding strategy for maximum noise tolerance bidirectional associative memory
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
FPGA Implementation of Parallel Alpha-Beta Associative Memories
ICIAR '08 Proceedings of the 5th international conference on Image Analysis and Recognition
Bidirectional associative memories: Different approaches
ACM Computing Surveys (CSUR)
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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, besides correct recall of noisy patterns, perfect recall of all trained patterns, with no ambiguity and no conditions. An example of fingerprint recognition is presented.