| Stability Analysis for Stochastic Delayed High-order Neural Networks |
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| 作者姓名： | 舒慧生 吕增伟 魏国亮 |
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| 作者单位： | [1]College of Sciences, Donghua University, Shanghai 200051 [2]College of Information Sciences and Technology, Donghua University, Shanghai 200051 |
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| 摘 要： | In this paper, the global asymptotic stability analysis problem is considered for a class of stochastic high-order neural networks with tin.delays. Based on a Lyapunov-Krasovskii functional and the stochastic stability analysis theory, several sufficient conditions are derived in order to guarantee the global asymptotic convergence of the equilibtium paint in the mean square. Investigation shows that the addressed stochastic highorder delayed neural networks are globally asymptotically stable in the mean square if there are solutions to some linear matrix inequalities （LMIs）. Hence, the global asymptotic stability of the studied stochastic high-order delayed neural networks can be easily checked by the Matlab LMI toolbox. A numerical example is given to demonstrate the usefulness of the proposed global stability criteria.
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| 关 键 词： | 神经网络 随机系统 时间延误 全局渐近稳定性 线性矩阵不等式 |
| 收稿时间： | 2006-02-22 |
Stability Analysis for Stochastic Delayed High-order Neural Networks |
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| SHU Hui-sheng,L Zeng-wei,WEI Guo-liang.Stability Analysis for Stochastic Delayed High-order Neural Networks[J].Journal of Donghua University,2006,23(1):73-77. |
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| Authors: | SHU Hui-sheng L Zeng-wei WEI Guo-liang |
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| Institution: | 1. College of Sciences, Donghua University, Shanghai 200051
2. College of Information Sciences and Technology, Donghua University, Shanghai 200051 |
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| Abstract: | In this paper, the global asymptotic stability analysis problem is considered for a class of stochastic high-order neural networks with time-delays. Based on a Lyapunov-Krasovskii functional and the stochastic stability analysis theory, several sufficient conditions are derived in order to guarantee the global asymptotic convergence of the equilibrium point in the mean square. Investigation shows that the addressed stochastic high-order delayed neural networks are globally asymptotically stable in the mean square if there are solutions to some linear matrix inequalities (LMIs). Hence, the global asymptotic stability of the studied stochastic high-order delayed neural networks can be easily checked by the Matlab LMI toolbox. A numerical example is given to demonstrate the usefulness of the proposed global stability criteria. |
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| Keywords: | high-order neural networks stochastic systems time delays Lyapunov-Krasovskii functional global asymptotic stability linear matrix inequality |
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