| Global exponential stability of reaction diffusion neural networks with discrete and distributed time-varying delays |
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| 作者姓名： | 张为元 李俊民 |
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| 作者单位： | School of Science,Xidian University Institute of Math.and Applied Math.,Xianyang Normal University |
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| 基金项目： | Project partially supported by the National Natural Science Foundation of China (Grant No. 60974139) and partially supported by the Fundamental Research Funds for the Central Universities. |
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| 摘 要： | This paper investigates the global exponential stability of reaction-diffusion neural networks with discrete and distributed time-varying delays.By constructing a more general type of Lyapunov-Krasovskii functional combined with a free-weighting matrix approach and analysis techniques,delay-dependent exponential stability criteria are derived in the form of linear matrix inequalities.The obtained results are dependent on the size of the time-varying delays and the measure of the space,which are usually less conservative than delay-independent and space-independent ones.These results are easy to check,and improve upon the existing stability results.Some remarks are given to show the advantages of the obtained results over the previous results.A numerical example has been presented to show the usefulness of the derived linear matrix inequality(LMI)-based stability conditions.
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| 关 键 词： | neural networks reaction-diffusion delays exponential stability |
| 收稿时间： | 7/7/2010 12:00:00 AM |
Global exponential stability of reaction–diffusion neural networks with discrete and distributed time-varying delays |
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| Zhang Wei-Yuan and Li Jun-Min.Global exponential stability of reaction diffusion neural networks with discrete and distributed time-varying delays[J].Chinese Physics B,2011,20(3):30701-030701. |
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| Authors: | Zhang Wei-Yuan and Li Jun-Min |
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| Institution: | School of Science, Xidian University, Xi'an 710071, China;Institute of Math. and Applied Math., Xianyang Normal University, Xianyang 712000, China;School of Science, Xidian University, Xi'an 710071, China |
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| Abstract: | This paper investigates the global exponential stability of reaction--diffusion neural networks with discrete and distributed time-varying delays. By constructing a more general type of Lyapunov--Krasovskii functional combined with a free-weighting matrix approach and analysis techniques, delay-dependent exponential stability criteria are derived in the form of linear matrix inequalities. The obtained results are dependent on the size of the time-varying delays and the measure of the space, which are usually less conservative than delay-independent and space-independent ones. These results are easy to check, and improve upon the existing stability results. Some remarks are given to show the advantages of the obtained results over the previous results. A numerical example has been presented to show the usefulness of the derived linear matrix inequality (LMI)-based stability conditions. |
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| Keywords: | neural networks reaction–diffusion delays exponential stability |
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