Global exponential stability in Lagrange sense for periodic neural networks with various activation functions

Authors:
Ailong Wu;Zhigang Zeng;Chaojin Fu;Wenwen Shen
Affiliations:
Department of Control Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China;Department of Control Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China;College of Mathematics and Statistics, Hubei Normal University, Huangshi 435002, China;Department of Control Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
Venue:
Neurocomputing
Year:
2011

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Abstract

In this paper, global exponential stability in Lagrange sense for periodic neural networks with various activation functions is further studied. By constructing appropriate Lyapunov-like functions, we provide easily verifiable criteria for the boundedness and global exponential attractivity of periodic neural networks. These theoretical analysis can narrow the search field of optimization computation, associative memories, chaos control and provide convenience for applications.