4.7 Article

Stochastic exponential synchronization of jumping chaotic neural networks with mixed delays

Journal

Publisher

ELSEVIER
DOI: 10.1016/j.cnsns.2011.07.024

Keywords

Stochastic exponential synchronization; Jumping chaotic neural networks; Jensen integral inequality; Lyapunov-Krasovskii functional; Finsler's Lemma

Funding

  1. National Natural Science Foundation of China [60774093]
  2. Specialized Research Fund for the Doctoral Program of Higher Education of China [200801451096]
  3. China Postdoctoral Science Foundation [20080431150, 200902547]
  4. National High Technology Research and Development Program [2009AA04Z127]
  5. Program for New Century Excellent Talents in University [NCET-08-0101]

Ask authors/readers for more resources

This paper deals with the exponential synchronization problem for a class of stochastic jumping chaotic neural networks with mixed delays and sector bounded nonlinearities. The mixed time delays under consideration comprise both discrete time-varying delays and distributed time delays. By applying the Finsler's Lemma and constructing appropriate Lyapunov-Krasovskii functional based on delay partitioning, several improved delay-dependent feedback controllers with sector nonlinearities are developed to achieve the synchronization in mean square in terms of linear matrix inequalities. It is established theoretically that two special cases of the obtained criteria are less conservative than some existing results but including fewer slack variables. As the present conditions involve no free weighting matrices, the computational burden is largely reduced. One numerical example is provided to demonstrate the effectiveness of the theoretical results. (C) 2011 Elsevier B.V. All rights reserved.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available