| Nonlinear H∞ control of structured uncertain stochastic neural networks with discrete and distributed time varying delays |
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| 引用本文： | 陈狄岚,张卫东. Nonlinear H∞ control of structured uncertain stochastic neural networks with discrete and distributed time varying delays[J]. 中国物理 B, 2008, 17(4): 1506-1512 |
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| 作者姓名： | 陈狄岚 张卫东 |
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| 作者单位： | Department of Automation,Shanghai Jiaotong University, Shanghai 200030, China；Division of Basic Courses, Shanghai Maritime University,Shanghai 200135, China;Department of Automation,Shanghai Jiaotong University, Shanghai 200030, China |
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| 基金项目： | Project is supported in part by theNational Natural Science Foundation of China (Grant No 60474031),NCET (04-0383), the State Key Development Program for Basic Researchof China (Grant No 2002cb312200-3), the Shanghai `Phosphor'Foundation (Grant No 04Q |
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| 摘 要： | This paper is concerned with the problem of robust H∞ control for structured uncertain stochastic neural networks with both discrete and distributed time varying delays. A sufficient condition is presented for the existence of H∞ control based on the Lyapunov stability theory. The stability criterion is described in terms of linear matrix inequalities （LMIs）, which can be easily checked in practice. An example is provided to demonstrate the effectiveness of the proposed result.
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| 关 键 词： | 非线性鲁棒控制 结构不确定性随机神经网络 李雅普诺夫函数 离散分布式时变延迟 |
Nonlinear Hinfty control of structured uncertain stochastic neural networks with discrete and distributed time varying delays |
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| Chen Di-Lan and Zhang Wei-Dong. Nonlinear Hinfty control of structured uncertain stochastic neural networks with discrete and distributed time varying delays[J]. Chinese Physics B, 2008, 17(4): 1506-1512 |
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| Authors: | Chen Di-Lan and Zhang Wei-Dong |
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| Affiliation: | [1]Department of Automation, Shanghai Jiaotong University, Shanghai 200030, China; [2]Division of Basic Courses, Shanghai Maritime University, Shanghai 200135, China |
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| Abstract: | This paper is concerned with the problem of robust Hinftycontrol for structured uncertain stochastic neural networks withboth discrete and distributed time varying delays. A sufficientcondition is presented for the existence of Hinfty controlbased on the Lyapunov stability theory. The stability criterion isdescribed in terms of linear matrix inequalities (LMIs), which canbe easily checked in practice. An example is provided to demonstratethe effectiveness of the proposed result. |
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| Keywords: | delayed neural networks (DNNs) stochastic systems Lyapunov functional linear matrix inequality |
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