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        High capacity associative memory with bipolar and binary, biased patterns

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        900839.pdf (PDF, 418Kb)
        Author
        Chen, W.
        Adams, R.G.
        Calcraft, L.
        Davey, N.
        Steuber, Volker
        Attention
        2299/769
        Abstract
        The high capacity associative memory model is interesting due to its significantly higher capacity when compared with the standard Hopfield model. These networks can use either bipolar or binary patterns, which may also be biased. This paper investigates the performance of a high capacity associative memory model trained with biased patterns, using either bipolar or binary representations. Our results indicate that the binary network performs less well under low bias, but better in other situations, compared with the bipolar network.
        Publication date
        2007
        Published in
        Proceedings of UKCI, London
        Other links
        http://hdl.handle.net/2299/769
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