Existence and global exponential stability of periodic solutions of recurrent cellular neural networks with impulses and delays

Authors:
Zhanji Gui;Xiao-Song Yang;Weigao Ge
Affiliations:
Department of Computer Science, Hainan Normal University, Haikou, Hainan 571158, PR China and Department of Mathematics, Huazhong University of Science and Technology, Wuhan 430074, PR China;Department of Mathematics, Huazhong University of Science and Technology, Wuhan 430074, PR China;Department of Applied Mathematics, Beijing Institute of Technology, Beijing 100081, PR China
Venue:
Mathematics and Computers in Simulation
Year:
2008

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Abstract

By using the continuation theorem of coincidence degree theory and constructing suitable Lyapunov functions, we study the existence, uniqueness and global exponential stability of periodic solutions for recurrent neural networks with impulsive perturbations and delays. Further, by using numerical simulation method, the influences of the impulsive perturbations on the inherent oscillations are investigated.