文献类型：期刊文献

英文题名：The stability of anti-periodic solutions for fractional-order inertial BAM neural networks with time-delays

作者：Zhang, Yuehong[1];Li, Zhiying[1];Jiang, Wangdong[1];Liu, Wei[1]

机构：[1]Shaoxing Univ, Yuanpei Coll, Shaoxing 312000, Peoples R China

年份：2023

卷号：8

期号：3

起止页码：6176

外文期刊名：AIMS MATHEMATICS

收录：SCI-EXPANDED(收录号：WOS:000909557600001)、、Scopus(收录号：2-s2.0-85146126321)、WOS

基金：The work was supported by Science Project of Zhejiang Educational Department (No. Y202145903) , the Ministry of Education's Cooperative Education Project (220603284143545) , Science Project of Shaoxing University (No. 2020LG1009) and Science Project of Shaoxing University Yuanpei College (KY2021C04) .

语种：英文

外文关键词：fractional -order; inertial BAM neural networks; Ascoli-Arzela theorem; anti -periodic; solutions; Mittag-Le ffl er stability

外文摘要：The dynamic signal transmission process can be regarded as an anti-periodic process, and fractional-order inertial neural networks are widely used in signal processing and other fields, so anti-periodicity is also regarded as an important dynamic feature of inertial neural networks. This paper mainly studies the existence and Mittag-Leffler stability of anti-periodic solutions for a class of fractional-order inertial BAM neural networks with time-delays. By introducing variable substitution, the model with two different fractional-order derivatives is transformed into a model with only one fractional-order derivative of the same order. Using the properties of fractional-order calculus, the relationship between the fractional-order integral of the state function with and without time-delays is given. Firstly, the sufficient conditions for the boundedness and the Mittag-Leffler stability of the solutions for the system are derived. Secondly, by constructing the sequence solution of the function for the system and applying Ascoli-Arzela theorem, the sufficient conditions for the existence and Mittag-Leffler stability of the anti-periodic solution are given. Finally, the correctness of the conclusion is verified by a numerical example.