文献类型：期刊文献

英文题名：Stability and existence of periodic solutions in inertial BAM neural networks with time delay

作者：Ke Yunquan[1];Miao Chunfang[1]

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

年份：2013

卷号：23

期号：3-4

起止页码：1089

外文期刊名：NEURAL COMPUTING & APPLICATIONS

收录：SCI-EXPANDED(收录号：WOS:000324794200053)、、EI(收录号：20134016797216)、Scopus(收录号：2-s2.0-84884591790)、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：BAM neural networks; Inertial term; Lyapunov function; Weierstrass criteria; Exponential stability

外文摘要：In this paper, the global exponential stability and existence of periodic solutions for inertial BAM neural networks are investigated. The system is transformed to first-order differential equation with chosen variable substitution. Then, some new sufficient conditions that ensure the existence and exponential stability of periodic solutions for the system are obtained by constructing suitable Lyapunov function, using Weierstrass criteria and boundedness of solutions. Finally, an example is given to illustrate the effectiveness of the results.