Lecture：Projective synchronization of a nonautonomous delayed neural networks with Caputo derivative

Lecturer: Wang Changyou (Professor)

Time: 16:00-18:00 pm, 29^thNov.

Venue: C302B Minglilou Building

Wang Changyou holds a PhD.in Applied Mathematics, and is currently a third-level professor, member of the Academic Committee and Teaching Guidance Committee, Director of the Academic Committee of the Applied Mathematics Center, and graduate supervisor at Chengdu University of Information Technology. He is also a commentator at theMathematical Reviewsin the United States. He has served as a director at the Chongqing Mathematical Society, a third-level professor at Chongqing University of Posts and Telecommunications, director of the Institute of Applied Mathematics, head of the Mathematics discipline, and graduate supervisor. As of now, he has published more than 120 papers in domestic and foreign journals such asApplied Mathematical Modeling,Applied Mathematics Letters,Journal of Mathematical Analysis and Applications,Physical A-Statistical Mechanics and Its Applications,International Journal of Biometics,Acta Mathematica Science (Series B),among which more than 40 papers were indexed by SCI. In addition, he has published one monograph at Science Press, and led 12 scientific research projects at or above the provincial level. He is currently in charge of one local-fund project guided by the central government in Sichuan Province. His main research interests include time-delay reaction-diffusion equations, differential equations, fractional differential equations, biological mathematics, image and video processing.

In this lecture, Professor Wang Changyou will be 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 researches 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.

Organizer and sponsor:

School of Sciences

Institute of Artificial Intelligence

Institute of Nonlinear Dynamical Systems

Mathematical Mechanics Research Center

Institute of Science and Technology Development