Neural network modeling

被引：4

作者：

Chakrabarti, Bikas K. ^{[1
]}

Basu, Abhik ^{[1
]}

机构：

[1] Saha Inst Nucl Phys, Ctr Appl Math & Computat Sci, Kolkata 700064, W Bengal, India

来源：

MODELS OF BRAIN AND MIND: PHYSICAL, COMPUTATIONAL AND PSYCHOLOGICAL APPROACHES | 2008年 / 168卷

关键词：

neural network models; spin glasses; associative memory; Hopfield model; Little model; retrieval dynamics; relaxation;

D O I：

10.1016/S0079-6123(07)68013-3

中图分类号：

Q189 [神经科学];

学科分类号：

071006 ;

摘要：

Some of the (comparatively older) numerical results on neural network models obtained by our group are reviewed. These models incorporate synaptic connections constructed by using the Hebb's rule. The dynamics is determined by the internal field which has a weighted contribution from the time delayed signals. Studies on relaxation and the growth of correlations in the Hopfield model are discussed here. The memory capacity of such networks have been investigated also for some asymmetric synaptic interactions. In some cases both the asynchronous (or Glauber; Hopfield) and synchronous (Little) dynamics are used. At the end, in the appendix, we discuss the effects of asymmetric interactions on the statistical properties in a related model of spin glass (new results).

引用

页码：155 / 168

页数：14

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