Statistical mechanics beyond the hopfield model: Solvable problems in neural network theory

被引：0

作者：

Coolen, ACC ^{[1
]}

Del Prete, V ^{[1
]}

机构：

[1] Kings Coll London, Dept Math, London WC2R 2LS, England

来源：

REVIEWS IN THE NEUROSCIENCES | 2003年 / 14卷 / 1-2期

关键词：

recurrent neural networks; self-programming; synchronization;

D O I：

暂无

中图分类号：

Q189 [神经科学];

学科分类号：

071006 ;

摘要：

We present four 'case study' examples of solvable problems in the theory of recurrent neural networks, which are relevant to our understanding of information processing in the brain, but which are also interesting from a purely statistical mechanical point of view, even at the level of simple models (which helps in stimulating interdisciplinary work). The examples concern issues in network dynamics, network connectivity, spike timing and synaptic plasticity.

引用

页码：181 / 193

页数：13

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