文献类型：期刊文献

英文题名：Anti-periodic Solutions of Inertial Neural Networks with Time Delays

作者：Ke, Yunquan[1];Miao, Chunfang[1]

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

年份：2017

卷号：45

期号：2

起止页码：523

外文期刊名：NEURAL PROCESSING LETTERS

收录：SCI-EXPANDED(收录号：WOS:000398721400010)、、EI(收录号：20163002647098)、Scopus(收录号：2-s2.0-84979221588)、WOS

语种：英文

外文关键词：Inertial term; Neural networks; Lyapunov method; Anti-periodic solutions; Exponential stability

外文摘要：In this paper, the exponential stability of anti-periodic solutions for inertial neural networks with time delays is investigated. First, by properly chosen variable substitution the system is transformed to first order differential equation. Second, some sufficient conditions which can ensure the existence and exponential stability of anti-periodic solutions for the system are obtained by using Lyapunov method and uniformly converges. Finally, an example is given to illustrate the effectiveness of the results.