报告题目: Projective synchronization of a nonautonomous delayed neural networks with Caputo derivative
报 告 人: 王长有 教授
报告时间: 2023年11月29日16：00-18：00
报告地点: 明理楼C302B
报告人简介:
王长有，博士，成都信息工程大学三级教授、学术委员会及教学指导委员会委员、应用数学中心学术委员会主任、研究生导师，美国数学评论 (Mathematical Reviews) 评论员，曾任重庆市数学学会理事，重庆邮电大学三级教授、应用数学研究所所长、数学学科负责人、研究生导师。在《Applied Mathematical Modelling》、《Applied Mathematics Letters》、《Journal of Mathematical Analysis and Applications》、《Physica A-Statistical Mechanics and Its Applications》、《International Journal of Biomathematics》、《Acta Mathematica Scientia, Series B》等国内外核心以上刊物发表学术论文120余篇，其中被SCI收录40余篇；在科学出版社出版学术专著1部；主持（或主研）省部级以上科研项目12项。目前主持四川省中央引导地方基金项目1项。主要研究领域包括：时滞反应扩散方程、差分方程、分数阶微分方程、生物数学、图像及视频处理。
报告内容摘要:
In this talk, we are mainly concerned with the projective synchronization problem of nonautonomous neural networks with time delay and Caputo derivative. First, by introducing time delay and variable coefficient into the known neural network model, the new neural network that can more accurately describe the interaction between neurons is given. Second, based on the improved neural network model, two global synchronization schemes are achieved, respectively. Finally, by constructing two novel Lyapunov functions and utilizing the properties of delay fractional-order differential inequalities, the asymptotic stability of the zero equilibrium point of the error system obtained from the master-slave systems is proved by some new developing analysis methods, respectively, and some criteria for global projective synchronization of delayed nonautonomous neural networks with Caputo derivatives are obtained, respectively, under two new synchronous controllers. In addition, the correctness of the theoretical results obtained in this paper is verified by some numerical simulation. As we all know, there have been a lot of research on the synchronization of integer (fractional) order autonomous neural network models with or without time delay. However, there is little research on the projective synchronization properties of non-autonomous (variable coefficient) neural network models with delay.
主办单位: 理学院､人工智能研究院､非线性动力系统研究所､
数理力学研究中心 ､科学技术发展研究院
