Entropy Based Associative Memory

Masahiro NAKAGAWA  

Publication
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E89-A   No.4   pp.895-901
Publication Date: 2006/04/01
Online ISSN: 1745-1337
DOI: 10.1093/ietfec/e89-a.4.895
Print ISSN: 0916-8508
Type of Manuscript: Special Section PAPER (Special Section on Selected Papers from the 18th Workshop on Circuits and Systems in Karuizawa)
Category: 
Keyword: 
entropy,  associative memory,  memory retrieval,  autocorrelation learning,  

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Summary: 
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.