| 时滞Hopfield神经网络的随机稳定性分析 |
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| 引用本文： | 王勇,蒋真,程思蔚. 时滞Hopfield神经网络的随机稳定性分析[J]. 计算机工程与应用, 2008, 44(16): 60-62. DOI: 10.3778/j.issn.1002-8331.2008.16.018 |
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| 作者姓名： | 王勇 蒋真 程思蔚 |
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| 作者单位： | 长沙理工大学,计算机与通信工程学院,长沙,410076;长沙理工大学,数学与计算科学学院,长沙,410076 |
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| 基金项目： | 湖南省自然科学基金 , 湖南省教育厅科研项目 |
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| 摘 要： | T-S模型提供了一种通过模糊集和模糊推理将复杂的非线性系统表示为线性子模型的方法。研究了时滞Hopfield神经网络的随机稳定性（SFVDHNNs）。首先描述了SFVDHNNs模型，然后用Lyapunov方法研究了SFVDHNNs全局均方指数稳定性，通过可以被一些标准的数值分析方法求解的线性矩阵不等式（LMIs）得出了稳定性标准。
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| 关 键 词： | 随机稳定性 Hopfield神经网络 均方指数稳定 时变系统 |
| 文章编号： | 1002-8331(2008)16-0060-03 |
| 收稿时间： | 2007-09-11 |
| 修稿时间： | 2007-09-11 |
Stochastic stability analysis of fuzzy Hopfield neural networks with time-varying delays |
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| WANG Yong,JIANG Zhen,CHENG Si-wei. Stochastic stability analysis of fuzzy Hopfield neural networks with time-varying delays[J]. Computer Engineering and Applications, 2008, 44(16): 60-62. DOI: 10.3778/j.issn.1002-8331.2008.16.018 |
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| Authors: | WANG Yong JIANG Zhen CHENG Si-wei |
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| Affiliation: | 1.College of Computer and Communication Engineering，Changsha University of Science and Technology，Changsha 410076，China 2.College of Mathematics and Calculation Science，Changsha University of Science and Technology，Changsha 410076，China |
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| Abstract: | The ordinary Takagi Sugeno(T-S) fuzzy models have provided an approach to represent complex nonlinear systems to a set of linear sub-models by using fuzzy sets and fuzzy reasoning.In this paper,stochastic fuzzy Hopfield neural networks with time-varying delays(SFVDHNNs) are studied.The model of SFVDHNN is first established,then,the global exponential stability in the mean square for SFVDHNN is studied by using the Lyapunov-Krasovskii approach.Stability criterion is derived in terms of Linear Matrix Inequalities(LMIs),which can be effectively solved by some standard numerical packages. |
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| Keywords: | stochastic stability Hopfield neural network exponential stability time-varying system |
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