Robust stability of delayed reaction-diffusion recurrent neural networks with Dirichlet boundary conditions on time scales

Authors:
Yongkun Li;Kaihong Zhao
Affiliations:
Department of Mathematics, Yunnan University, Kunming, Yunnan 650091, People's Republic of China;Department of Mathematics, Yunnan University, Kunming, Yunnan 650091, People's Republic of China and Department of Applied Mathematics, Kunming University of Science and Technology, Kunming, Yunna ...
Venue:
Neurocomputing
Year:
2011

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Abstract

In this paper, the global robust exponential stability of equilibrium solution to delayed reaction-diffusion recurrent neural networks with Dirichlet boundary conditions on time scales is studied. Using topological degree theory, M-matrix method, Lyapunov functional and inequality skills, we establish some sufficient conditions for the existence, uniqueness and global robust exponential stability of equilibrium solution to delayed reaction-diffusion recurrent neural networks with Dirichlet boundary conditions on time scales. One example is given to illustrate the effectiveness of our results.