Bidirectional associative memories
IEEE Transactions on Systems, Man and Cybernetics
International Journal of Man-Machine Studies - Special Issue: Knowledge Acquisition for Knowledge-based Systems. Part 5
Non-holographic associative memory
Neurocomputing: foundations of research
Issues in Bayesian analysis of neural network models
Neural Computation
Storage capacity of non-monotonic neurons
Neural Networks
Better learning for bidirectional associative memory
Neural Networks
An overview of character recognition focused on off-line handwriting
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
On the problem of spurious patterns in neural associative memory models
IEEE Transactions on Neural Networks
A feedforward bidirectional associative memory
IEEE Transactions on Neural Networks
Memory annihilation of structured maps in bidirectional associative memories
IEEE Transactions on Neural Networks
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In this work, we study the behaviour of the Bidirectional Associative Memory (BAM) in terms of the supporting neural structure, with a view to its possible improvements as a useful Pattern Classifier by means of class associations from unknown inputs, once mentioned classes have been previously defined by one or even more prototypes. The best results have been obtained by suitably choosing the training pattern pairs, the thresholds, and the activation functions of the network's neurones, by means of certain proposed methods described in the paper. In order to put forward the advantages of these proposed methods, the classifier has been applied on an especially popular hand-written character set as the well-known NIST#19 character database, and with one of the UCI's data bases. In all cases, the method led to a marked improvement in the performance achievable by a BAM, with a 0% error rate.