On permutation symmetries of hopfield model neural network

Jiyang Dong, Shenchu Xu, Zhenxiang Chen and Boxi Wu

Discrete Dynamics in Nature and Society, 2001, vol. 6, 1-8

Abstract:

Discrete Hopfield neural network (DHNN) is studied by performing permutation operations on the synaptic weight matrix. The storable patterns set stored with Hebbian learning algorithm in a network without losing memories is studied, and a condition which makes sure all the patterns of the storable patterns set have a same basin size of attraction is proposed. Then, the permutation symmetries of the network are studied associating with the stored patterns set. A construction of the storable patterns set satisfying that condition is achieved by consideration of their invariance under a point group.

Date: 2001
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnddns:458198

DOI: 10.1155/S1026022601000139

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