State estimation of recurrent neural networks with interval time-varying delay: an improved delay-dependent approach

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• 作者：Yang Dongsheng ; Xinrui Liu ; Yukun Xu ; Yingchun Wang…
• 关键词：Delay ; dependent ; Recurrent neural networks ; State estimation ; Interval time ; varying delay ; Linear matrix inequality (LMI)
• 刊名：Neural Computing & Applications
• 出版年：2013
• 出版时间：September 2013
• 年：2013
• 卷：23
• 期：3-4
• 页码：1149-1158
• 全文大小：481KB
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• 作者单位：Yang Dongsheng (1)
  Xinrui Liu (1)
  Yukun Xu (1)
  Yingchun Wang (1)
  Zhaobing Liu (1)
  
  1. College of Information Science and Engineering, Shenyang, China
  
• ISSN：1433-3058

文摘

This paper is concerned with the state estimation problem for a class of recurrent neural networks with interval time-varying delay, where time delay includes either slow or fast time-varying delay. A novel delay-dependent criterion, in which the rate–range of time delay is also considered, is established to estimate the neuron states through available output measurements such that, for all admissible time delays, the dynamics of the estimation error system is globally asymptotically stable. The proposed method is based on a new Lyapunov–Krasovskii functional with triple-integral terms and free-weighting matrix approach. Numerical examples are given to illustrate the effectiveness of the method.