文献类型：期刊文献

英文题名：MEMORY PATTERN ANALYSIS OF BAM NEURAL NETWORKS WITH TIME-DELAY

作者：Ke, Yunquan[1];Miao, Chun-Fang[1]

机构：[1]Shaoxing Univ, Dept Math, Shaoxing 312000, Peoples R China

年份：2009

卷号：19

期号：3

起止页码：843

外文期刊名：INTERNATIONAL JOURNAL OF BIFURCATION AND CHAOS

收录：SCI-EXPANDED(收录号：WOS:000266507100005)、、EI(收录号：20092812185535)、Scopus(收录号：2-s2.0-67649858472)、WOS

基金：?This work is supported by the National Natural Science Foundation of China (No. 10871226, No. 10875078)

语种：英文

外文关键词：BAM neural networks; memory patterns; equilibrium point; exponentially stable

外文摘要：In this paper, memory patterns of bidirectional associative memory (BAM) neural networks with time-delay are investigated based on stability theory. Several sufficient conditions are obtained such that the equilibrium point is locally exponentially stable when the point is located at the designated position. These conditions, which can be directly derived from the synaptic connection weights and the external input of the BAM neural networks, are very easy to be verified. In addition, three examples are given to show the effectiveness of the results.