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具混合时滞的随机神经网络的稳定性分析 被引量：3

The stability analysis for a general class of stochastic neural networks with mixed time delays
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摘要 通过构造新的Lyapunov-Krasovskii泛函并利用随机分析的方法,建立了一类具有混合时滞和马尔可夫(Markovian)参数切换的随机神经网络均方渐近稳定的判据.所考虑的混合时滞既包含时变的离散时滞也包含无穷分布时滞,神经网络的参数切换由某个马尔可夫链所确定. By employing new Lyapunov-Krasovskii functionals and conducting stochastic analysis,it is to establish easily verifiable conditions under which the stochastic neural network with mixed time delays and Markovian switching is asymptotically stable in the mean square in the presence of parameters uncertainties.The mixed time delays under consideration comprise both the discrete time-varying delays and the infinitely distributed time-delays,and the Markovian switching is according to a Markovian chain.
作者 张金
机构地区 宿迁高等师范学校数学系
出处 《苏州大学学报（自然科学版）》 CAS 2011年第2期16-22,共7页 Journal of Soochow University(Natural Science Edition)
关键词 随机神经网络 混合时滞 无穷分布时滞 马尔可夫参数切换 渐近稳定性 stochastic neural networks mixed time delays infinitely distributed time delays Markovian switching asymtotic stability
分类号 O175.1 [理学—基础数学]
  • 相关文献

参考文献9

  • 1Wang Z,Liu Y,Liu X.On global asymptotic stability of neural networks with discrete and distributed delays[J].Physics Letters A,2005,345 (4/6):299-308.
  • 2Huang H,Ho D W C,Lam.J.Stochastic stability analysis of fuzzy Hopfield neural networks with time-varying delays[J].IEEE Trans Circuits and Systems:Part Ⅱ,2005,52(5):251 -255.
  • 3Wang Z,Liu Y,Li M,et al.Stability analysis for stochastic Cohen-Grossberg neural networks with mixed time delays[J].IEEE Trans Neural Networks,2006,17(3):814 -820.
  • 4Wang Z,Liu Y,Fraser K,et al.Stochastic stability of uncertain Hopfield neural networks with discrete and distributed delays[J].Physics Letters A,2006,354(4):288 -297.
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同被引文献23

  • 1Ca J, Huang D-S, Qu Y. Global robust stability of delayed recurrent neural networks.Chaos[J]. Solitons & Fractals, 2005, 23(1): 221-229.
  • 2Cao J, Song Q. Stability in Cohen-Grossberg-type bidirectional associative memory neural networks with time-varying delays[J]. Nonlinearity, 2006, 19(7): 1601-1617.
  • 3Cao J, Ho D W C. A general framework for global asymptotic stability analysis of delayed neural networks based on LMI approach[J]. Chaos, Solitons&Fractals, 2005, 24(5): 1317-1329.
  • 4Song Q, Zhao Z, Li Y. Global exponential stability of BAM neural networks with distributed delays and reaction-diffusion terms[J]. Physics LettersA, 2005, 335(2-3): 213-225.
  • 5Song Q, Cao J. 0 Periodic solutions and its exponential stability of reaction-diffusion recurrent neural networks with continuously distributed delays[J]. Nonlinear Analysis - Real World Applications, 2006, 7(1): 65-80.
  • 6Wang Z, Liu Y, Liu X. On global asymptotic stability of neural networks with discrete and distributed delays[J]. Physics Letters A, 2005, 345(4-6), 299-308.
  • 7Wang Z, Liu Y and Liu X. On global asymptotic stability of neural networks with discrete and distributed delays[J]. Physics Letters A, 2005, 345(4-6): 299-308.
  • 8Huang H, Ho D W C, and Lam J. Stochastic stability analysis of fuzzy Hopfield neural networks with time-varying delays[J]. IEEE Trans Circuits and Systems: Part II, 2005, 52(5): 251-255.
  • 9Wang Z, Liu Y, Li M, and Liu X. Stability analysis for stochastic Cohen-Grossberg neural networks with mixed time delays[J]. IEEE Trans Neural Networks, 2006, 17(3): 814-820.
  • 10Wang Z, Liu Y, Fraser K, and Liu X. Stochastic stability of uncertain Hopfield neural networks with discrete and distributed delays[J]. Physics Letters A, 2006, 354(4): 288-297.

引证文献3

苏州大学学报（自然科学版）
2011年 第2期

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