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        High Performance Associative Memories and Structured Weight Dilution

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        102096.pdf (PDF, 424Kb)
        Author
        Turvey, S.P.
        Hunt, S.
        Davey, N.
        Frank, R.
        Attention
        2299/3973
        Abstract
        The consequences of two techniques for symmetrically diluting the weights of the standard Hopfield architecture associative memory model, trained using a non-Hebbian learning rule, are examined. This paper reports experimental investigations into the effect of dilution on factors such as: pattern stability and attractor performance. It is concluded that these networks maintain a reasonable level of performance at fairly high dilution rates.
        Publication date
        2004
        Published in
        Applications and Science in Soft Computing - Advances in Intelligent and Soft Computing , Vol. 24
        Other links
        http://hdl.handle.net/2299/3973
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