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  • 标题:A study on state estimation for discrete-time recurrent neural networks with leakage delay and time-varying delay
  • 本地全文:下载
  • 作者:Sai-Bing Qiu ; Xin-Ge Liu ; Yan-Jun Shu
  • 期刊名称:Advances in Difference Equations
  • 印刷版ISSN:1687-1839
  • 电子版ISSN:1687-1847
  • 出版年度:2016
  • 卷号:2016
  • 期号:1
  • 页码:234
  • DOI:10.1186/s13662-016-0958-4
  • 语种:English
  • 出版社:Hindawi Publishing Corporation
  • 摘要:We investigate state estimation for a class of discrete-time recurrent neural networks with leakage delay and time-varying delay. The design method for the state estimator to estimate the neuron states through available output measurements is given. A novel delay-dependent sufficient condition is obtained for the existence of state estimator such that the estimation error system is globally asymptotically stable. Based a novel double summation inequality and reciprocally convex approach, an improved stability criterion is obtained for the error-state system. Two numerical examples are given to demonstrate the effectiveness of the proposed design methods. The simulation results show that the leakage delay has a destabilizing influence on a neural network system.
  • 关键词:state estimation ; discrete-time ; leakage delay ; stability
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