Global Mittag-Leffler Synchronization of Fractional-Order Neural Networks Via Impulsive Control

被引：0
|
作者：
Xujun Yang
Chuandong Li
Tingwen Huang
Qiankun Song
Junjian Huang
机构：
[1] Southwest University,Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing, College of Electronic and Information Engineering
[2] Texas A&M University at Qatar,College of Mathematics and Statistics
[3] Chongqing Jiaotong University,Department of Computer Science
[4] Chongqing University of Education,undefined
来源：
Neural Processing Letters | 2018年 / 48卷
关键词：
Fractional-order neural networks; Impulse; Mittag-Leffler synchronization; Lyapunov direct method; -matrix;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
This paper aims at analyzing the impulsive synchronization of fractional-order neural works. Firstly, in view of control theory, by constructing a suitable impulsive response system with the designed controller, the synchronization error system between the drive system and the corresponding response system is given. Afterwards, based on the theory of impulsive differential equation, the theory of fractional differential equation, Lyapunov direct method, and inequality techniques, some effective sufficient criteria are established to guarantee the global Mittag-Leffler stability for the synchronization error system. Finally, several simulation examples are designed to demonstrate the effectiveness and feasibility of the obtained results.
引用
收藏
页码：459 / 479
页数：20
相关论文
共 50 条
  • [21] Global Mittag-Leffler projective synchronization for fractional-order neural networks: an LMI-based approach
    Wu, Huaiqin
    Wang, Lifei
    Wang, Yu
    Niu, Peifeng
    Fang, Bolin
    [J]. ADVANCES IN DIFFERENCE EQUATIONS, 2016,
  • [22] Mittag-Leffler stability of fractional-order Hopfield neural networks
    Zhang, Shuo
    Yu, Yongguang
    Wang, Hu
    [J]. NONLINEAR ANALYSIS-HYBRID SYSTEMS, 2015, 16 : 104 - 121
  • [23] Global Mittag-Leffler Synchronization of Fractional-Order Neural Networks With Time-Varying Delay via Hybrid Sliding Mode Control
    Yang, Fangyan
    Chen, Lijuan
    [J]. IEEE ACCESS, 2020, 8 : 177471 - 177480
  • [24] Global Mittag-Leffler boundedness and synchronization for fractional-order chaotic systems
    Jian, Jigui
    Wu, Kai
    Wang, Baoxian
    [J]. PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2020, 540
  • [25] Mittag-Leffler stability and adaptive impulsive synchronization of fractional order neural networks in quaternion field
    Pratap, Anbalagan
    Raja, Ramachandran
    Alzabut, Jehad
    Cao, Jinde
    Rajchakit, Grienggrai
    Huang, Chuangxia
    [J]. MATHEMATICAL METHODS IN THE APPLIED SCIENCES, 2020, 43 (10) : 6223 - 6253
  • [26] Globally β-Mittag-Leffler stability and β-Mittag-Leffler convergence in Lagrange sense for impulsive fractional-order complex-valued neural networks
    Li, Hui
    Kao, Yonggui
    Li, Hong-Li
    [J]. CHAOS SOLITONS & FRACTALS, 2021, 148
  • [27] Mittag-Leffler stability analysis on variable-time impulsive fractional-order neural networks
    Yang, Xujun
    Li, Chuandong
    Song, Qiankun
    Huang, Tingwen
    Chen, Xiaofeng
    [J]. NEUROCOMPUTING, 2016, 207 : 276 - 286
  • [28] The Boundedness and the Global Mittag-Leffler Synchronization of Fractional-Order Inertial Cohen–Grossberg Neural Networks with Time Delays
    Zhiying Li
    Yuehong Zhang
    [J]. Neural Processing Letters, 2022, 54 : 597 - 611
  • [29] LMI conditions to global Mittag-Leffler stability of fractional-order neural networks with impulses
    Wu, Huaiqin
    Zhang, Xinxin
    Xue, Shunhui
    Wang, Lifei
    Wang, Yu
    [J]. NEUROCOMPUTING, 2016, 193 : 148 - 154
  • [30] Global Mittag-Leffler stabilization of fractional-order bidirectional associative memory neural networks
    Wu, Ailong
    Zeng, Zhigang
    Song, Xingguo
    [J]. NEUROCOMPUTING, 2016, 177 : 489 - 496
12345