Stability Analysis of Quaternion-Valued Neutral Neural Networks with Generalized Activation Functions

被引:3
|
作者
Wu, Yanqiu [1 ]
Tu, Zhengwen [1 ]
Dai, Nina [2 ]
Wang, Liangwei [1 ]
Hu, Ning [3 ]
Peng, Tao [1 ]
机构
[1] Chongqing Three Gorges Univ, Sch Math & Stat, Wanzhou 404100, Peoples R China
[2] Chongqing Three Gorges Univ, Sch Elect & Informat Engn, Wanzhou 404100, Peoples R China
[3] Chongqing Three Gorges Univ, Expt & Practice Ctr, Wanzhou 404100, Peoples R China
基金
中国国家自然科学基金;
关键词
Quaternion-valued neutral neural networks (QVNNNs); Stability; Wirtinger-based inequality; Reciprocally convex inequality; Neutral delay; GLOBAL EXPONENTIAL STABILITY; TIME-VARYING DELAYS; SYNCHRONIZATION; DISCRETE; CRITERIA;
D O I
10.1007/s12559-023-10212-w
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Stability is a central issue in the study of dynamical systems, and quaternion-valued neural networks (QVNNs) perform well in handling the problem involving high-dimension date. The paper is dedicated to investigating the stability problem of QVNNs with neutral delay. In order to accurately estimate the derivative of Lyapunov functional, both reciprocally convex inequality and Wirtinger-based inequality are extended to the quaternion domain. And the direct quaternion method is used to analyze the quaternion-valued neutral neural networks (QVNNNs). Based on the generalized inequalities, the existence, uniqueness, and global stability criteria for QVNNS with several freedom matrices are derived. Concision and compact stability criteria of QVNNNs are established in the form of quaternion-valued LMIs, and the correctness of the theoretical results was verified through a numerical example.
引用
收藏
页码:392 / 403
页数:12
相关论文
共 50 条
  • [31] Design and Analysis of Quaternion-Valued Neural Networks for Associative Memories
    Chen, Xiaofeng
    Song, Qiankun
    Li, Zhongshan
    IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2018, 48 (12): : 2305 - 2314
  • [32] Synchronization criteria for neutral-type quaternion-valued neural networks with mixed delays
    Li, Shuang
    Wang, Xiao-mei
    Qin, Hong-ying
    Zhong, Shou-ming
    AIMS MATHEMATICS, 2021, 6 (08): : 8044 - 8063
  • [33] Mutiple ψ-type stability of fractional-order quaternion-valued neural networks
    Udhayakumar, K.
    Rakkiyappan, R.
    Li, Xiaodi
    Cao, Jinde
    APPLIED MATHEMATICS AND COMPUTATION, 2021, 401
  • [34] Exponential Stability Analysis of Mixed Delayed Quaternion-Valued Neural Networks Via Decomposed Approach
    Wang, Huamin
    Tan, Jie
    Wen, Shiping
    IEEE ACCESS, 2020, 8 : 91501 - 91509
  • [35] Stability analysis for quaternion-valued inertial memristor-based neural networks with time delays
    Liu, Weide
    Huang, Jianliang
    Yao, Qinghe
    NEUROCOMPUTING, 2021, 448 : 67 - 81
  • [36] Robust stability analysis of impulsive quaternion-valued neural networks with distributed delays and parameter uncertainties
    Zhou, Jielin
    Tan, Yuanshun
    Chen, Xiaofeng
    Liu, Zijian
    ADVANCES IN DIFFERENCE EQUATIONS, 2021, 2021 (01)
  • [37] Robust stability analysis of impulsive quaternion-valued neural networks with distributed delays and parameter uncertainties
    Jielin Zhou
    Yuanshun Tan
    Xiaofeng Chen
    Zijian Liu
    Advances in Difference Equations, 2021
  • [38] Effect of Impulses on Robust Exponential Stability of Delayed Quaternion-Valued Neural Networks
    Xu, Xiaohui
    Yang, Jibin
    Yang, Haolin
    Sun, Shulei
    NEURAL PROCESSING LETTERS, 2023, 55 (07) : 9615 - 9634
  • [39] Stop and go strategy for Lagrange stability of quaternion-valued memristive neural networks
    Li, Ruoxia
    Cao, Jinde
    Li, Ning
    MATHEMATICAL METHODS IN THE APPLIED SCIENCES, 2023, 46 (06) : 6578 - 6589
  • [40] Further research on exponential stability for quaternion-valued neural networks with mixed delays
    Xu, Xiaohui
    Xu, Quan
    Yang, Jibin
    Xue, Huanbin
    Xu, Yanhai
    NEUROCOMPUTING, 2020, 400 : 186 - 205