Passivity of Inertial Neural Networks With Delays on Time Scales

被引：1
作者：
Xiao, Qiang [1 ]
Wang, Lingyu [2 ]
Huang, Tingwen [3 ]
机构：
[1] Hamad Bin Khalifa Univ, Coll Sci & Engn, Doha, Qatar
[2] Jimei Univ, Sch Sci, Xiamen, Peoples R China
[3] Texas A&M Univ Qatar, Dept Math, Doha, Qatar
来源：
2017 13TH INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND SECURITY (CIS) | 2017年
关键词：
Passivity; inertial neural networks; delay; time scale; VARYING DELAYS; STABILITY; SYNCHRONIZATION; SYSTEMS; MULTIPERIODICITY;
D O I：
10.1109/CIS.2017.00048
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper deals with the passivity problem of inertial neural networks (INNs) with discrete delays on time scales. By one linear variable transformation, one passivity criterion is obtained based on the calculus of time scale and LMI techniques Furthermore, two particular criteria for the corresponding continuous and discrete time INNs are derived. Some numerical examples are given to show the validity of the obtained results. The time scale scheme offers results that hold for continuous-time systems, discrete-time systems, and the systems that involve on time intervals.
引用
收藏
页码：187 / 191
页数：5
相关论文
共 50 条
  • [21] Passivity of Switched Recurrent Neural Networks With Time-Varying Delays
    Lian, Jie
    Wang, Jun
    [J]. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2015, 26 (02) : 357 - 366
  • [22] Global Exponential Stability and Synchronization for Discrete-Time Inertial Neural Networks With Time Delays: A Timescale Approach
    Xiao, Qiang
    Huang, Tingwen
    Zeng, Zhigang
    [J]. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2019, 30 (06) : 1854 - 1866
  • [23] Passivity Analysis of Dynamic Neural Networks with Different Time-scales
    Wen Yu
    Xiaoou Li
    [J]. Neural Processing Letters, 2007, 25 : 143 - 155
  • [24] Global exponential synchronization of nonautonomous recurrent neural networks with time delays on time scales
    Wang, Lingyu
    Huang, Tingwen
    Xiao, Qiang
    [J]. APPLIED MATHEMATICS AND COMPUTATION, 2018, 328 : 263 - 275
  • [25] New passivity results for uncertain discrete-time stochastic neural networks with mixed time delays
    Li, Hongyi
    Wang, Chuan
    Shi, Peng
    Gao, Huijun
    [J]. NEUROCOMPUTING, 2010, 73 (16-18) : 3291 - 3299
  • [26] Passivity Analysis of Non-autonomous Discrete-Time Inertial Neural Networks with Time-Varying Delays
    Xuan Chen
    Dongyun Lin
    [J]. Neural Processing Letters, 2020, 51 : 2929 - 2944
  • [27] Passivity and Passification of Memristor-Based Recurrent Neural Networks With Time-Varying Delays
    Guo, Zhenyuan
    Wang, Jun
    Yan, Zheng
    [J]. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2014, 25 (11) : 2099 - 2109
  • [28] New passivity criteria for memristive uncertain neural networks with leakage and time-varying delays
    Xiao, Jianying
    Zhong, Shouming
    Li, Yongtao
    [J]. ISA TRANSACTIONS, 2015, 59 : 133 - 148
  • [29] Passivity and robust passivity of stochastic reaction-diffusion neural networks with time-varying delays
    Sheng, Yin
    Zeng, Zhigang
    [J]. JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS, 2017, 354 (10): : 3995 - 4012
  • [30] Passivity analysis of uncertain neural networks with mixed time-varying delays
    Kwon, O. M.
    Park, M. J.
    Park, Ju H.
    Lee, S. M.
    Cha, E. J.
    [J]. NONLINEAR DYNAMICS, 2013, 73 (04) : 2175 - 2189
12345