Uniform stability of Fractional Order Leaky Integrator Echo State Neural Network with multiple time delays

被引：38
作者：
Pahnehkolaei, Seyed Mehdi Abedi [1 ]
Alfi, Alireza [1 ]
Tenreiro Machado, J. A. [2 ]
机构：
[1] Shahrood Univ Technol, Fac Elect & Robot Engn, Shahrood 3619995161, Iran
[2] Polytech Porto, Inst Engn, Dept Elect Engn, Rua Dr Antonio Bernardino de Almeida 431, P-4249015 Oporto, Portugal
来源：
INFORMATION SCIENCES | 2017年 / 418卷
关键词：
Fractional order neural network; Echo state; Time delay; Stability; Contraction mapping; DYNAMICS; CLASSIFICATION; DISSIPATIVITY; CALCULUS; SYSTEMS;
D O I：
10.1016/j.ins.2017.08.046
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 uniform stability of the Fractional Order Leaky Integrator Echo State Neural Network (FOESN) with multiple delays. The delays occur in the transmission, the readout and the leakage of the network and have constant values. Sufficient conditions for uniform intrinsical stability of such networks in the presence of delays are provided. The intrinsical stability guarantees the FOESN is stable independently of the delays. In addition, the existence and uniqueness of the equilibrium point using the contraction mapping theorem are derived. Simulation results illustrate the effectiveness of the proposed method. (C) 2017 Elsevier Inc. All rights reserved.
引用
收藏
页码：703 / 716
页数：14
相关论文
共 50 条
  • [11] Fractional Order Echo State Network for Time Series Prediction
    Yao, Xianshuang
    Wang, Zhanshan
    NEURAL PROCESSING LETTERS, 2020, 52 (01) : 603 - 614
  • [12] Positivity and Stability of Fractional-Order Coupled Neural Network with Time-Varying Delays
    Gong, Jiyun
    Qiu, Hongling
    Shen, Jun
    ELECTRONICS, 2023, 12 (23)
  • [13] The modified sufficient conditions for echo state property and parameter optimization of leaky integrator echo state network
    Lun, Shu-xian
    Hu, Hai-feng
    Yao, Xian-shuang
    APPLIED SOFT COMPUTING, 2019, 77 : 750 - 760
  • [14] Existence and Uniform Stability Analysis of Fractional-Order Complex-Valued Neural Networks With Time Delays
    Rakkiyappan, R.
    Cao, Jinde
    Velmurugan, G.
    IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2015, 26 (01) : 84 - 97
  • [15] On Finite-Time Stability for Fractional-Order Neural Networks with Proportional Delays
    Xu, Changjin
    Li, Peiluan
    NEURAL PROCESSING LETTERS, 2019, 50 (02) : 1241 - 1256
  • [16] Dynamical complexity of a fractional-order neural network with nonidentical delays: Stability and bifurcation curves
    Mo, Shansong
    Huang, Chengdai
    Li, Huan
    Wang, Huanan
    MATHEMATICAL METHODS IN THE APPLIED SCIENCES, 2024, 47 (09) : 7764 - 7779
  • [17] Stability and Hopf bifurcation analysis of fractional-order complex-valued neural networks with time delays
    Rakkiyappan, R.
    Udhayakumar, K.
    Velmurugan, G.
    Cao, Jinde
    Alsaedi, Ahmed
    ADVANCES IN DIFFERENCE EQUATIONS, 2017,
  • [18] A stability criterion for discrete-time fractional-order echo state network and its application
    Yao, Xianshuang
    Wang, Zhanshan
    Huang, Zhanjun
    SOFT COMPUTING, 2021, 25 (06) : 4823 - 4831
  • [19] Fractional order uncertain BAM neural networks with mixed time delays : An existence and Quasi-uniform stability analysis
    Chinnamuniyandia, Maharajan
    Chandranb, Sowmiya
    Xu, Changjin
    JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2024, 46 (02) : 4291 - 4313
  • [20] Uniform Stability Analysis of Fractional-Order BAM Neural Networks with Delays in the Leakage Terms
    Yang, Xujun
    Song, Qiankun
    Liu, Yurong
    Zhao, Zhenjiang
    ABSTRACT AND APPLIED ANALYSIS, 2014,
12345