4.7 Article

Stability analysis for discrete-time Markovian jump neural networks with mixed time-delays

Journal

EXPERT SYSTEMS WITH APPLICATIONS
Volume 39, Issue 6, Pages 6174-6181

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.eswa.2011.11.111

Keywords

Neural networks; Markovian jumping parameters; Mixed time-delays; Piecewise homogeneous; Globally asymptotically stable

Funding

  1. National Creative Research Groups Science Foundation of China [60721062]
  2. National High Technology Research and Development Program of China [2006AA04 Z182]
  3. National Natural Science Foundation of PR China [60736021]

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The problem of delay-dependent stability analysis is investigated for discrete-time Markovian jump neural networks with mixed time-delays (both discrete and infinity-distributed time delays). The Markov chain in the underlying neural networks is finite piecewise homogeneous. A delay-dependent condition is derived for the addressed neural networks to be globally asymptotically stable. As an extension, we further consider the stability analysis problem for the same type of neural networks but with partially known transition probabilities. Two numerical examples are given to demonstrate the usefulness of the derived methods. (C) 2011 Elsevier Ltd. All rights reserved.

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