文献类型：期刊文献

英文题名：Pattern memory analysis of second-order 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：2011

卷号：217

期号：22

起止页码：8883

外文期刊名：APPLIED MATHEMATICS AND COMPUTATION

收录：SCI-EXPANDED(收录号：WOS:000290902600002)、、EI(收录号：20112214012498)、Scopus(收录号：2-s2.0-79957466361)、WOS

基金：This work is supported by the Natural Science Foundation of Zhejiang Province (No. Y6100096), and the National Natural Science Foundation of China (No. 10871226, No. 10875078).

语种：英文

外文关键词：The second-order neural networks; Saturation regions; Patterns memory; Exponential stable

外文摘要：In this paper, the pattern memory of the second-order neural networks with time-delay are investigated based on the stability theory. Several sufficient conditions are obtained such that the equilibrium point is locally exponential stable when the equilibrium point located in the saturation region. These conditions can be directly derived from the synaptic connection weights and the external input of the second-order neural networks, and be verified easily. In addition, four examples are given to show the effectiveness of the results. (C) 2011 Elsevier Inc. All rights reserved.