DELAY-INDEPENDENT STABILITY IN BIDIRECTIONAL ASSOCIATIVE MEMORY NETWORKS

被引：514

作者：

GOPALSAMY, K

HE, XZ

机构：

[1] School of Information Science Technology, Finders University, Adelaide

来源：

IEEE TRANSACTIONS ON NEURAL NETWORKS | 1994年 / 5卷 / 06期

关键词：

D O I：

10.1109/72.329700

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

It is shown that if the neuronal gains are small compared with the synaptic connection weights, then a bidirectional associative memory network with axonal signal transmission delays converges to the equilibria associated with exogenous inputs to the network; both discrete and continuously distributed delays are considered; the asymptotic stability is global in the state space of neuronal activations and also is independent of the delays.

引用

页码：998 / 1002

页数：5

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