Bidirectional associative memories
IEEE Transactions on Systems, Man and Cybernetics
Neural computing: theory and practice
Neural computing: theory and practice
Introduction to the theory of neural computation
Introduction to the theory of neural computation
Better learning for bidirectional associative memory
Neural Networks
A Bidirectional Associative Memory Based on Optimal Linear Associative Memory
IEEE Transactions on Computers
An analysis of high-capacity discrete exponential BAM
IEEE Transactions on Neural Networks
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This paper presents a study of the model of triple BAM by [11] which is an improved variation of the original BAM model by [7]. This class of model aims at integrating different sensory inputs in order to memorize a unified and distributed representation. An experimental evaluation of the model is presented that underlines its limitations in terms of noise robustness and learning capacities. A new model is presented in order to overcome those initial limitations by introducing a new online learning algorithm adapted from the PRLAB initial algorithm that improve both noise robustness and learning capacities. Finally, model properties and limitations are considered and discussed within the context of multi-modal integration and brain modeling.