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2007

Sparsely-connected associative memory models with displaced connectivity

8 years 10 months ago
Sparsely-connected associative memory models with displaced connectivity
Abstract. Our work is concerned with finding optimum connection strategies in highperformance 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.
Lee Calcraft, Rod Adams, Neil Davey
Added 29 Oct 2010
Updated 29 Oct 2010
Type Conference
Year 2007
Where ESANN
Authors Lee Calcraft, Rod Adams, Neil Davey
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