Synergetic computers and cognition: a top-down approach to neural nets
Synergetic computers and cognition: a top-down approach to neural nets
Entropy Based Associative Memory
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
IEEE Transactions on Computers
Representation of Associated Data by Matrix Operators
IEEE Transactions on Computers
Auto-associative memory with two-stage dynamics of nonmonotonic neurons
IEEE Transactions on Neural Networks
A Generalised Entropy Based Associative Model
Neural Information Processing
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In this paper, an entropy based associative memory model will be proposed and applied to memory retrievals with an orthogonal learning model to compare with the conventional autoassociative model with a quadratic Lyapunov functionals. In the present approach, the updating dynamics will be constructed on the basis of the entropy minimization strategy which may be reduced asymptotically to the autocorrelation dynamics as a special case. From numerical results, it will be found that the presently proposed novel approach realizes the larger memory capacity in comparison with the autocorrelation model based on dynamics such as associatron according to the higher-order correlation involved in the proposed dynamics.