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Markov切换的脉冲随机泛函微分方程的指数稳定性

Exponential stability of ISFDEs with Markov switching
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摘要 研究了一类具有Markov切换的脉冲随机泛函微分方程的全局p阶指数稳定性。通过利用Ito公式,引入一类特殊的Lyapunov函数,运用数学分析方法、Rzauminkin-型方法和不等式技巧建立了该系统全局p阶矩指数的稳定性定理,获得了其p阶矩Lyapunov指数的上限,改善和推广了相关文献的结果,并通过一个实例说明了本文结论具有更低的保守性。 A class of impulsive stochastic functional differential equations with Markov switching is investigated.Based on It formula and by introducing a class of special Lyapunov functions and applying mathematical analysis method,Lyapunov-Razumikhin method and combing with inequality technique,some novel sufficient conditions are derived to ensure the p th moment exponential stability of the trivial solution.A numerical example is given to illustrate the effectiveness and lower conservation.
作者 杨树杰 毛凯 陈涵 YANG Shujie;MAO Kai;CHEN Han(Institute of System Science and Mathematics,Naval Aeronautical University,Yantai 264001,China;Troops 91576 of People’s Liberation Army,Ningbo 315000,China)
出处 《黑龙江大学自然科学学报》 CAS 2019年第5期551-557,共7页 Journal of Natural Science of Heilongjiang University
基金 山东省自然科学基金资助项目(ZR2014AM006)
关键词 泛函微分方程的指数稳定性 Markov切换 LYAPUNOV函数 Rzauminkin-型方法 Exponential stability of functional differential equations Markov switching Lyapunov functions Rzauminkin method
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  • 1XI FuBao Department of Mathematics, Beijing Institute of Technology, Beijing 100081, China.Feller property and exponential ergodicity of diffusion processes with state-dependent switching[J].Science China Mathematics,2008,51(3):329-342. 被引量:2
  • 2JIANG Hai-jun, TENG Zhi-dong. Dynamics of neural networks with variable coefficients and time-varying delays[ J]. Neural networks, 2006, 19 (5) :676-683.
  • 3XU Sheng-yuan, LAM J. A new approach to exponential stability analysis of neural networks with time-varying delays [ J]. Neural networks, 2006, 19(1) :76-83.
  • 4SONG Qian-kun. Exponential stability of recurrent neural networks with both time - varying delays and general activation functions via LMI ap- proach [ J]. Neurocomputing, 2008, 71 ( 13 - 15) :2823 - 2830.
  • 5SU Wei-wei, CHEN Yi-ming. Global robust exponential stability analysis for stochastic interval neural networks with time - varying delays [ J ]. Communications in Nonlinear Science and Numerical Simulation, 2009,14 (5) :2293 -2300.
  • 6ZHANG Bao-yong, XU Sheng-yuan, ZOU Yun. Improved delay-dependent exponential stability criteria for discrete-time recurrent neural networks with time-varying delays[ J]. Neurocomputing, 2008,71 ( 1 - 3 ) : 321 - 330.
  • 7ZHANG Hua-guang, WANG Gang. New criteria of global exponential stability for a class of generalized neural networks with time-varying delays [ J ]. Neurocomputing, 2007, 70 ( 13 - 15 ) :2486 - 2494.
  • 8SONG Chun-wei, GAO Hui-jun, ZHENG Wei-xing. A new approach to stability analysis of discrete-time recrrent neural networks with time-varying delay[J]. Neurocomputing, 2009, 72( 10-12) :2563-2568.
  • 9LIU Yu-rong, WANG Zi-dong, LIU Xiao-hui. Robust stability of discrete -time stochastic neural networks systems with time-varying delays[ J]. Neurocomputing, 2008, 71 (4 - 6 ) :823 - 833.
  • 10SONG Qian-kun, LIANG Jin-ling, WANG Zi-dong. Passivity analysis of discrete-time stochastic neural networks with time-varying delays [ J ]. Neurocomoutin. 2009, 72 (7 - 9 ) : 1782 - 1788.

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