New Stabilization Method for Delayed Discrete-Time Cohen-Grossberg BAM Neural Networks

被引：7
作者：
Cong, Er-Yong [1 ,3 ]
Han, Xiao [3 ]
Zhang, Xian [2 ]
机构：
[1] Harbin Univ, Dept Math, Harbin 150086, Peoples R China
[2] Heilongjiang Univ, Sch Math Sci, Harbin 150080, Peoples R China
[3] Jilin Univ, Sch Math, Changchun 130012, Peoples R China
来源：
IEEE ACCESS | 2020年 / 8卷
关键词：
Control theory; Stability; Delays; State feedback; Biological neural networks; Closed loop systems; Discrete-time Cohen-Grossberg BAM neural network; stabilization; global exponential stability; GLOBAL EXPONENTIAL STABILITY; ASYMPTOTIC STABILITY;
D O I：
10.1109/ACCESS.2020.2997905
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper deals with the state feedback stabilization problem of delayed discrete-time Cohen-Grossberg BAM neural networks. By the mathematical induction method, stabilizable conditions are derived to ensure that the resulting closed-loop system is globally exponentially stable, and thereby, the desired state feedback controller is designed. These stabilizable conditions are very simple, which can easily verified by using the standard toolbox software (for example, MATLAB). The proposed approach is directly based on the definition of global exponential stability, and does not involve the construction of any Lyapunov-Krasovskii functional. For a special case, it is theoretical proven that the proposed method is superior to an existing one. Moreover, several illustrative examples are given to validate the success of the derived theoretical results.
引用
收藏
页码：99327 / 99336
页数：10
相关论文
共 50 条
  • [21] Stability and bifurcation for discrete-time Cohen-Grossberg neural network
    Zhao, Hongyong
    Wang, Lei
    APPLIED MATHEMATICS AND COMPUTATION, 2006, 179 (02) : 787 - 798
  • [22] Robust stability of delayed fuzzy Cohen-Grossberg neural networks
    Huang, Tingwen
    COMPUTERS & MATHEMATICS WITH APPLICATIONS, 2011, 61 (08) : 2247 - 2250
  • [23] Existence and stability of periodic solutions of discrete-time Cohen-Grossberg neural networks with delays and impulses
    Wang, Jinling
    Jiang, Haijun
    Hu, Cheng
    NEUROCOMPUTING, 2014, 142 : 542 - 550
  • [24] Dynamic analysis of periodic solution for high-order discrete-time Cohen-Grossberg neural networks with time delays
    Sun, Kaiyun
    Zhang, Ancai
    Qiu, Jianlong
    Chen, Xiangyong
    Yang, Chengdong
    Chen, Xiao
    NEURAL NETWORKS, 2015, 61 : 68 - 74
  • [25] Stability Analysis on Discrete-Time Cohen-Grossberg Neural Networks with Bounded Distributed Delay
    Li Tao
    Wang Ting
    Fei Shumin
    2011 30TH CHINESE CONTROL CONFERENCE (CCC), 2011, : 1081 - 1086
  • [26] Dynamics of delayed Cohen-Grossberg neural networks
    Chang, Ancheng
    Peng, Changlin
    Huang, Chuangxia
    CONFERENCE ON MODELING, IDENTIFICATION AND CONTROL, 2012, 3 : 254 - 261
  • [27] Equilibria and Stability Analysis of Cohen-Grossberg BAM Neural Networks on Time Scale
    Mingshuo Liu
    Yong Fang
    Huanhe Dong
    Journal of Systems Science and Complexity, 2022, 35 : 1348 - 1373
  • [28] Existence and stability of periodic solutions for impulsive fuzzy BAM Cohen-Grossberg neural networks on time scales
    Cai, Shaohong
    Zhang, Qianhong
    ADVANCES IN DIFFERENCE EQUATIONS, 2016,
  • [29] Stability analysis of fuzzy Markovian jumping Cohen-Grossberg BAM neural networks with mixed time-varying delays
    Sathy, R.
    Balasubramaniam, P.
    COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION, 2011, 16 (04) : 2054 - 2064
  • [30] Stability analysis of Takagi-Sugeno fuzzy Cohen-Grossberg BAM neural networks with discrete and distributed time-varying delays
    Balasubramaniam, P.
    Ali, M. Syed
    MATHEMATICAL AND COMPUTER MODELLING, 2011, 53 (1-2) : 151 - 160
12345