Abstract
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 model based on the quadratic Lyapunov functional to be minimized. 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 above-mentioned autocorrelation dynamics as a special case. From numerical results, it will be found that the presently proposed novel approach realizes twice of the memory capacity in comparison with the autocorrelation based dynamics such as associatron.
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