Journal
NONLINEAR ANALYSIS-REAL WORLD APPLICATIONS
Volume 13, Issue 5, Pages 2259-2270Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.nonrwa.2012.01.021
Keywords
Delayed recurrent neural network; Time varying delay; Impulse control; Linear matrix inequality; Exponential stability; Markovian jump parameter
Categories
Funding
- National Natural Science Foundation of China [10801056, 11072059]
- Natural Science Foundation of Ningbo [2010A610094]
- Specialized Research Fund for the Doctoral Program of Higher Education [20110092110017]
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This paper is concerned with the stability of delayed recurrent neural networks with impulse control and Markovian jump parameters. The jumping parameters are modeled as a continuous-time, discrete-state Markov process. By applying the Lyapunov stability theory, Dynkin's formula and linear matrix inequality technique, some new delay-dependent conditions are derived to guarantee the exponential stability of the equilibrium point. Moreover, three numerical examples and their simulations are given to show the less conservatism and effectiveness of the obtained results. In particular, the traditional assumptions on the differentiability of the time varying delays and the boundedness of their derivatives are removed since the time varying delays considered in this paper may not be differentiable, even not continuous. (C) 2012 Elsevier Ltd. All rights reserved.
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