Global Mean Square Exponential Stability of Memristor-Based Stochastic Neural Networks with Time-Varying Delays

被引：0
|
作者：
Xu, Xiao-Lin [1 ]
机构：
[1] Hubei Normal Univ, Coll Comp Sci & Technol, Huangshi 435002, Hubei, Peoples R China
来源：
CURRENT TRENDS IN COMPUTER SCIENCE AND MECHANICAL AUTOMATION, VOL 1 | 2017年
关键词：
memristor-based neural networks; stochastic systems; mean square exponential stability; nonsmooth analysis; SYNCHRONIZATION;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
In this paper, we study the global mean square exponential stability of memristor-based stochastic neural networks with time-varying delays by the means of Lyapunov function and ito formula. Meanwhile, one of the central ideas of this paper is that the theory of differential equations about discontinuous right-hand sides is applied. The proposed exponential stability criteria extend and improve some existing works. A numerical example is given to verify the results.
引用
收藏
页码：270 / 279
页数：10
相关论文
共 50 条
  • [31] A Representation of System Solutions for Global Exponential Stabilization of Memristor-Based Neural Networks With Unbounded Time-Varying Delays
    Meng, Xianhe
    Zhang, Xian
    Wang, Yantao
    Liu, Chunyan
    IEEE ACCESS, 2021, 9 : 118107 - 118112
  • [32] Mean square exponential stability in high-order stochastic impulsive neural networks with time-varying delays
    Gu H.
    Jiang H.
    Teng Z.
    Journal of Applied Mathematics and Computing, 2009, 30 (1-2) : 151 - 170
  • [33] Mean-square exponential stability of stochastic Hopfield neural networks with time-varying discrete and distributed delays
    Ma, Li
    Da, Feipeng
    PHYSICS LETTERS A, 2009, 373 (25) : 2154 - 2161
  • [34] Mean square exponential stability of stochastic high-order Hopfield neural networks with time-varying delays
    Shi, Xiangdong
    SENSORS, MEASUREMENT AND INTELLIGENT MATERIALS, PTS 1-4, 2013, 303-306 : 1532 - 1535
  • [35] Mean square exponential stability of stochastic fuzzy Hopfield neural networks with discrete and distributed time-varying delays
    Li, Hongyi
    Chen, Bing
    Lin, Chong
    Zhou, Qi
    NEUROCOMPUTING, 2009, 72 (7-9) : 2017 - 2023
  • [36] Relaxed exponential passivity criteria for memristor-based neural networks with leakage and time-varying delays
    Xiao, Jianying
    Zhong, Shouming
    Li, Yongtao
    Xu, Fang
    INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS, 2017, 8 (06) : 1875 - 1886
  • [37] Exponential synchronization of quaternion-valued memristor-based neural networks with time-varying delays
    Cheng, Yanzhao
    Shi, Yanchao
    INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, 2023, 37 (07) : 1762 - 1781
  • [38] Relaxed exponential passivity criteria for memristor-based neural networks with leakage and time-varying delays
    Jianying Xiao
    Shouming Zhong
    Yongtao Li
    Fang Xu
    International Journal of Machine Learning and Cybernetics, 2017, 8 : 1875 - 1886
  • [39] Global Mean Square Fxponential Synchronization of Stochastic Neural Networks with Time-Varying Delays
    Wu, Yinzhe
    Zhong, Jie
    Liu, Ling
    2017 NINTH INTERNATIONAL CONFERENCE ON ADVANCED COMPUTATIONAL INTELLIGENCE (ICACI), 2017, : 108 - 114
  • [40] Mean square exponential stability of uncertain stochastic neural networks with time-varying delay
    Wu, Yuanyuan
    Wu, Yuqiang
    Chen, Yonggang
    NEUROCOMPUTING, 2009, 72 (10-12) : 2379 - 2384
12345