Delay-dependent state estimation for delayed neural networks

Yong He, Qing Guo Wang, Min Wu, Chong Lin

Research output: Contribution to journalArticlepeer-review

212 Citations (Scopus)


In this letter, the delay-dependent state estimation problem for neural networks with time-varying delay is investigated. A delay-dependent criterion is established to estimate the neuron states through available output measurements such that the dynamics of the estimation error is globally exponentially stable. The proposed method is based on the free-weighting matrix approach and is applicable to the case that the derivative of a time-varying delay takes any value. An algorithm is presented to compute the state estimator. Finally, a numerical example is given to demonstrate the effectiveness of this approach and the improvement over existing ones.

Original languageEnglish
Pages (from-to)1077-1081
Number of pages5
JournalIEEE Transactions on Neural Networks
Issue number4
Publication statusPublished - Jul 2006
Externally publishedYes


  • Delay-dependent
  • Linear matrix inequality (LMI)
  • Neural networks
  • State estimation

ASJC Scopus subject areas

  • Software
  • Computer Science Applications
  • Computer Networks and Communications
  • Artificial Intelligence


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