2025-6-21- 13
Home > Archive>Volume 11, Issue 4, 2019 >440-445. DOI:10.13878/j.cnki.jnuist.2019.04.012
PDF HTML XML Export Cite reminder
H∞ state estimation of static neural networks with leakage delay
Author:
  • Article
    • | |
  • Metrics
    • |
  • Reference [12]
    • |
  • Related [20]
    • | | |
  • Comments
    Abstract:

    This paper focuses on the study of H∞ state estimation of static neural networks having leakage delay.With the skills to construct Lyapunov-Krasovskii functionals,a state estimator is designed for the estimation of H∞ performance,and the results are derived without applying differentiability on time-varying delays.Finally,a numerical example is provided to demonstrate the effectiveness and advantages of the obtained results.

    Reference
    [1] Lee W I,Lee S Y,Park P.A combined reciprocal convexity approach for stability analysis of static neural networks with interval time-varying delays[J].Neurocomputing,2017,221:168-177
    [2] Huang B N,Zhang H G,Gong D W,et al.Synchronization analysis for static neural networks with hybrid couplings and time delays[J].Neurocomputing,2015,148:288-293
    [3] Zeng H B,Park J H,Zhang C F,et al.Stability and dissipativity analysis of static neural networks with interval time-varying delay[J].Journal of the Franklin Institute,2015,352(3):1284-1295
    [4] Liu Y C,Wang T,Chen M S,et al.Dissipativity-based state estimation of delayed static neural networks[J].Neurocomputing,2017,247:137-143
    [5] Huang Z K,Li X Z,Mohamad S,et al.Robust stability analysis of static neural network with S-type distributed delays[J].Applied Mathematical Modelling,2009,33(2):760-769
    [6] Hu M F,Cao J D,Hu A H.Mean square exponential stability for discrete-time stochastic switched static neural networks with randomly occurring nonlinearities and stochastic delay[J].Neurocomputing,2014,129:476-481
    [7] Senthilraj S,Raja R,Zhu Q X,et al.New delay-interval-dependent stability criteria for static neural networks with time-varying delays[J].Neurocomputing,2016,186:1-7
    [8] Manivannan R,Panda S,Chong K T,et al.An arcak-type state estimation design for time-delayed static neural networks with leakage term based on unified criteria[J].Neural Networks,2018,106:110-126
    [9] Huang H,Feng G,Cao J D.Guaranteed performance state estimation of static neural networks with time-varying delay[J].Neurocomputing,2011,74(4):606-616
    [10] Duan Q H,Su H Y,Wu Z G.H∞ state estimation of static neural networks with time-varying delay[J].Neurocomputing,2012,97:16-21
    [11] Gu K Q,Kharitonov V L,Chen J.Stability of time-delay systems[M].Boston,MA:Birkhäuser Boston,2003.DOI:10.1007/978-1-4612-0039-0
    [12] Park P,Ko J W,Jeong C.Reciprocally convex approach to stability of systems with time-varying delays[J].Automatica,2011,47(1):235-238
    Cited by
Get Citation

WU Shuchen, LI Xiaodi.H∞ state estimation of static neural networks with leakage delay[J]. Journal of Nanjing University of Information Science & Technology,2019,11(4):440-445

Copy
Related Videos

Share
Article Metrics
  • Abstract:511
  • PDF: 1833
  • HTML: 0
  • Cited by: 0
History
  • Received:June 27,2019
  • Online: September 03,2019
Article QR Code

Address：No. 219, Ningliu Road, Nanjing, Jiangsu Province

Postcode：210044

Phone：025-58731025