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Application of an evolution strategy to the Hopfield model of associative memory

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2 Author(s)
Imada, A. ; Graduate Sch. of Inf. Sci., Nara Inst. of Sci. & Technol., Japan ; Araki, K.

We apply evolutionary computations to Hopfield's neural network model of associative memory. In the Hopfield model, an almost infinite number of combinations of synaptic weights gives a network an associative memory function. Furthermore, there is a trade-off between the storage capacity and the size of the basin of attraction. Therefore, the model can be thought of as a test suite of multi-modal and/or multi-objective function optimizations. As a preliminary stage, we investigate the basic behavior of an associative memory under simple evolutionary processes. In this paper, we present some experiments using an evolution strategy

Published in:

Evolutionary Computation, 1997., IEEE International Conference on

Date of Conference:

13-16 Apr 1997