文献类型：期刊文献

英文题名：The anti-periodic solutions of incommensurate fractional-order Cohen-Grossberg neural network with inertia

作者：Li, Zhiying[1];Liu, Wei[1]

机构：[1]Shaoxing Univ, Yuanpei Coll, Dept Math, Qunxian Middle Rd 2799, Shaoxing 312000, Zhejiang, Peoples R China

年份：2025

卷号：10

期号：2

起止页码：3180

外文期刊名：AIMS MATHEMATICS

收录：SCI-EXPANDED(收录号：WOS:001454262300005)、、Scopus(收录号：2-s2.0-85219319508)、WOS

基金：The authors declare they have not used Artificial Intelligence (AI) tools in the creation of this article. This research was funded on the Ministry of Education Industry-University Co-operation Collaborative Education Project (No. 220505876312732) , the Science Project of Zhejiang Educational Department (Y202454310) .

语种：英文

外文关键词：incommensurate; fractional-order; Cohen-Grossberg neural networks; anti-periodic solution; global asymptotical stability

外文摘要：A class of incommensurate fractional-order Cohen-Grossberg neural networks with inertia was investigated in this paper. First, the sufficient conditions for the boundedness of the solutions of the system were derived using the properties of fractional-order calculus. Second, by constructing a sequence of solutions in the system and using the Ascoli-Arzela theorem, the sufficient conditions for the existence of an anti-period solution and the global asymptotical stability of the system were deduced. Finally, the correctness of theoretical reasoning results was verified by a numerical simulation.