Global exponential robust stability of Cohen-Grossberg neural network with time-varying delays and reaction-diffusion terms |
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| Authors: | Qiankun Song |
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| Institution: | a Department of Mathematics, Chongqing Jiaotong University, Chongqing 400074, China
b Department of Mathematics, Southeast University, Nanjing 210096, China |
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| Abstract: | In this paper, the global exponential robust stability is investigated for Cohen-Grossberg neural network with time-varying delays and reaction-diffusion terms, this neural network contains time-invariant uncertain parameters whose values are unknown but bounded in given compact sets. Neither the boundedness and differentiability on the activation functions nor the differentiability on the time-varying delays are assumed. By using general Halanay inequality and M-matrix theory, several new sufficient conditions are obtained to ensure the existence, uniqueness, and global exponential robust stability of equilibrium point for Cohen-Grossberg neural network with time-varying delays and reaction-diffusion terms. Several previous results are improved and generalized, and three examples are given to show the effectiveness of the obtained results. |
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| Keywords: | Global exponential robust stability Cohen-Grossberg neural network Time-varying delays Reaction-diffusion terms |
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