文献类型：期刊文献

英文题名：Mittag-Leffler Stability and Global Asymptotically omega-Periodicity of Fractional-Order BAM Neural Networks with Time-Varying Delays

作者：Zhou, Fengyan[1];Ma, Chengrong[2]

机构：[1]Shaoxing Univ, Dept Math, Shaoxing 312000, Zhejiang, Peoples R China;[2]Shaoxing Univ, Coll Civil Engn, Shaoxing 312000, Zhejiang, Peoples R China

年份：2018

卷号：47

期号：1

起止页码：71

外文期刊名：NEURAL PROCESSING LETTERS

收录：SCI-EXPANDED(收录号：WOS:000426688200005)、、EI(收录号：20172203719413)、Scopus(收录号：2-s2.0-85019664491)、WOS

基金：The work is supported by the National Natural Science Foundation of China (No. 11675112) and Natural Science Foundation of Zhejiang Province (No. LY16A050001). The authors would like to thank the editor and three anonymous reviewers for their valuable suggestions and comments.

语种：英文

外文关键词：Fractional-order system; BAM neural networks; Time-varying delays; Mittag Leffler stability; S-asymptotical omega-periodicity; Global asymptotically omega-periodicity

外文摘要：This article studies the Mittag-Leffler stability and global asymptotical -periodicity for a class of fractional-order bidirectional associative memory (BAM) neural networks with time-varying delays by using Laplace transform, stability theory of fractional systems and some integration technique. Firstly, some sufficient conditions are given to ensure the boundedness and global Mittaag-Leffler stability of fractional-order BAM neural networks with time-varying delays. Next, S-asymptotical -periodicity and global asymptotical -periodicity of fractional-order BAM neural networks with time-varying delays are also explored. Finally, some numerical examples and simulation are performed to show the effectiveness of theoretical results.