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        Sparsely-connected associative memory models with displaced connectivity.

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        900844.pdf (PDF, 378Kb)
        Author
        Calcraft, L.
        Adams, R.G.
        Davey, N.
        Attention
        2299/764
        Abstract
        Our work is concerned with finding optimum connection strategies in high-performance associative memory models. Taking inspiration from axonal branching in biological neurons, we impose a displacement of the point of efferent arborisation, so that the output from each node travels a certain distance before branching to connect to other units. This technique is applied to networks constructed with a connectivity profile based on Gaussian distributions, and the results compared to those obtained with a network containing purely local connections, displaced in the same manner. It is found that displacement of the point of arborisation has a very beneficial effect on the performance of both network types, with the displaced locally-connected network performing the best.
        Publication date
        2007
        Other links
        http://hdl.handle.net/2299/764
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