Finite-time state estimation for delayed Hopfield neural networks with Markovian jump

被引：23
|
作者：
Wang, Tianbo [1 ]
Zhao, Shouwei [1 ]
Zhou, Wuneng [2 ]
Yu, Weiqin [1 ]
机构：
[1] Shanghai Univ Engn Sci, Coll Fundamental Studies, Shanghai 201620, Peoples R China
[2] Donghua Univ, Coll Informat Sci & Technol, Shanghai 200051, Peoples R China
来源：
NEUROCOMPUTING | 2015年 / 156卷
基金：
中国国家自然科学基金;
关键词：
Finite-time state estimation; Hopfield neural network; Time delay; Markov jump; DEPENDENT EXPONENTIAL STABILITY; VARYING DELAY; UNCERTAIN PARAMETERS; SYSTEMS; SYNCHRONIZATION; STABILIZATION;
D O I：
10.1016/j.neucom.2014.12.062
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, the finite-time state estimation problem of delayed Hopfield neural networks with Markovian jump is investigated. The activation functions are assumed to satisfy the section condition. A discontinuous estimator is designed through available output measurements such that the estimation error converges to the origin in finite time. The conditions that the desired estimator parameters need to satisfy are derived by using the Lyapunov stability theory and inequality technique. These conditions are provided in terms of the linear matrix inequalities. Finally, the effectiveness of the proposed method is illustrated by means of a numerical example. (C) 2015 Elsevier B.V. All rights reserved.
引用
下载
收藏
页码：193 / 198
页数：6
相关论文
共 50 条
  • [1] Exploring the finite-time dissipativity of Markovian jump delayed neural networks
    Sathishkumar, V. E.
    Vadivel, R.
    Cho, Jaehyuk
    Gunasekaran, Nallappan
    ALEXANDRIA ENGINEERING JOURNAL, 2023, 79 : 427 - 437
  • [2] Robust finite-time state estimation of uncertain neural networks with Markovian jump parameters
    Yao, Deyin
    Lu, Qing
    Wu, Chengwei
    Chen, Ziran
    NEUROCOMPUTING, 2015, 159 : 257 - 262
  • [3] State estimation for Markovian jump Hopfield neural networks with mixed time delays
    Guo, Lili
    Huang, Wanhui
    FRONTIERS IN PHYSICS, 2024, 12
  • [4] Finite-Time Arcak-Type State Estimation of Delayed Markovian Jumping Static Neural Networks
    Huang, He
    2017 4TH INTERNATIONAL CONFERENCE ON INFORMATION, CYBERNETICS AND COMPUTATIONAL SOCIAL SYSTEMS (ICCSS), 2017, : 572 - 577
  • [5] Finite-Time State Estimation for Delayed Neural Networks With Redundant Delayed Channels
    Zhao, Zhongyi
    Wang, Zidong
    Zou, Lei
    Guo, Ge
    IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2021, 51 (01): : 441 - 451
  • [6] Finite-Time State Estimation for Coupled Markovian Neural Networks With Sensor Nonlinearities
    Wang, Zhuo
    Xu, Yong
    Lu, Renquan
    Peng, Hui
    IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2017, 28 (03) : 630 - 638
  • [7] Finite-time state estimation of stochastic switched delayed neural networks
    Qiu Houming
    Chen Yun
    Yang Lele
    PROCEEDINGS OF THE 36TH CHINESE CONTROL CONFERENCE (CCC 2017), 2017, : 1977 - 1982
  • [8] Robust finite-time state estimation for uncertain discrete-time Markovian jump neural networks with two delay components
    Zhou, Xiaoqing
    Zhu, Quanxin
    NEUROCOMPUTING, 2018, 283 : 64 - 72
  • [9] Asynchronous finite-time state estimation for semi-Markovian jump neural networks with randomly occurred sensor nonlinearities
    Wang, Yao
    Xu, Shengyuan
    Li, Yongmin
    Chu, Yuming
    Zhang, Zhengqiang
    NEUROCOMPUTING, 2021, 432 : 240 - 249
  • [10] Asynchronous finite-time state estimation for semi-Markovian jump neural networks with randomly occurred sensor nonlinearities
    Wang, Yao
    Xu, Shengyuan
    Li, Yongmin
    Chu, Yuming
    Zhang, Zhengqiang
    Neurocomputing, 2021, 432 : 240 - 249
12345