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混合变时滞细胞神经网络的全局渐近稳定性 被引量：1

Globally Asymptotic Stability of Cellular Neural Networks with Hybrid Time-variable Delays
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摘要 基于微分动力系统Lyapunov稳定性理论和线性矩阵不等式(LMI)处理方法,借助于Matlab中LMI控制工具箱,给出了一类含有离散时滞和分布时滞的混合变时滞细胞神经网络的全局渐近稳定性的充分条件,改进了文献[9]的结果,降低了系统的保守性.数值例子进一步验证了结果的有效性. Based on the Lyapunov functional stability analysis for differential dynamic systems and the linear matrix inequality approach, a novel sufficient condition for cellular neural networks with hybrid discrete and distributed delays is derived to guarantee global asymptotic stability by using the linear matrix inequality （LMI） framework in Matlab. The criterion improved the result of reference [2] and has less conservation. A numerical example is given to show the effectiveness of our results.
作者 方胜乐 江明辉 邓修成
机构地区 三峡大学理学院
出处 《三峡大学学报（自然科学版）》 CAS 2008年第1期89-92,共4页 Journal of China Three Gorges University：Natural Sciences
基金 国家自然科学基金(600574025) 湖北省教育厅自然科学基金(Q200713001) 湖北省教育厅科研项目(D200613002)
关键词 细胞神经网络 渐近稳定性 LYAPUNOV泛函 线性矩阵不等式 cellular neural networks asymptotic stability Lyapunov function linear matrix inequality
分类号 N941.3 [自然科学总论—系统科学]
  • 相关文献

参考文献9

  • 1Cha L O, Yang L. Cellular Neural Network: Theory [J]. IEEE Trans Cire Syst, 1988, 35:1257-1272.
  • 2Park J H. Global Exponential Stability of Cellular Neural Networks with Variable Delays[J]. Applied Mathematics and Computation, 2006,183 : 1214-1219.
  • 3Lien C. Global Asymptotic Stability for Cellular Neural Networks with Discrete and Distributed Time-varying Delays[J]. Chaos,Solitons and Fractals, 2007, 34:1213- 1219.
  • 4Cao J. Global Asymptotic Stability of Neural Networks with Transmission Delays[J]. Int J Syst Sci, 2000, 31 ; 1313-1316.
  • 5Boyd B. Linear Matrix Inequalities in Systems and Control Theory[M]. Philadelphia: SIAM, 1994.
  • 6Burton T. Stability and Periodic Solutions of Ordinary Differential Equations and Functional Differential Equations[M]. Academic Press,1985.
  • 7Gu K. An Integral Inequality in the Stability Problem of Time-Delay Systems [J]. Proc IEEE CDC, Australia. December 2000, 2805-2810.
  • 8Liu Y. Global Exponential Stability of Generalized Recurrent Neural Networks with Discrete and Distributed Delays[J]. Neural Networks, 2006,19: 667-675.
  • 9Park J H. On Global Stability Criterion for Neural Networks with Discrete and Distributed Delays[J]. Chaos, Solitons and Fractals,2006, 30 : 897-902.

同被引文献7

  • 1Rakkiyappan R, Balasubramaniam P. New global exponential stability results for neutral-type neural networks with distributed time delays[J]. Neurocomputing, 2008,71 (4-6) : 1039-1045.
  • 2Rakkiyappan R, Balasubramaniam P. LMI conditions for global asymptotic stability results for neutral-type neural networks with distributed time delays [J]. Applied Mathematics and Computation, 2008,204 (1): 317-324.
  • 3Zhang J, Suda Y, Iwasa T. Absolutely exponential stability of a class of neural networks with unbounded delay[J]. Neural Networks, 2004, 17: 391-397.
  • 4Cao J. Global asymptotic stability of neural networks with transmission delays[J]. Int J Syst Sci, 2000, 31: 1313-1316.
  • 5Liao X F, Chen G R, Sanchez E N, Delay-dependent exponential stability analysis of delayed neural networks an LMI approach [J]. Neural Networks, 2002, 15: 855-866.
  • 6Xu S, Lain J, Ho D W C, Zou Y. Delay-dependent exponential stability for a class of neural networks with time delays [J]. J Comput Math Appl, 2005, 183: 16-28.
  • 7孟益民,甄铁军.具连续分布时滞细胞神经网络的指数稳定性[J].湖南大学学报（自然科学版）,2008,35(1):89-92. 被引量：2

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三峡大学学报（自然科学版）
2008年 第1期

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