Journal
NONLINEAR DYNAMICS
Volume 67, Issue 1, Pages 829-845Publisher
SPRINGER
DOI: 10.1007/s11071-011-0029-z
Keywords
pth moment exponential synchronization; Time-varying delay; Stochastic neural network; Cohen-Grossberg neural network; Markovian switching
Categories
Funding
- National Natural Science Foundation of China [10801056, 60874088]
- Natural Science Foundation of Ningbo [2010A610094]
- Ningbo University
- Specialized Research Fund for the Doctoral Program of Higher Education [20070286003]
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This paper is a contribution to the analysis of the pth moment exponential synchronization problem for a class of stochastic delayed Cohen-Grossberg neural networks with Markovian switching. The jumping parameters are determined by a continuous-time, discrete-state Markov chain, and the delays are time-varying delays. By using the Lyapunov-Krasovskii functional, stochastic analysis theory, a generalized Halanay-type inequality as well as output coupling with delay feedback control technique, some novel sufficient conditions are derived to achieve complete pth moment exponential synchronization of the addressed neural networks. In particular, the traditional assumptions on the differentiability of the time varying delay and the boundedness of its derivative are removed in this paper. The results obtained in this paper generalize and improve many known results. Moreover, a numerical example and its simulation are also provided to demonstrate the effectiveness and applicability of the theoretical results.
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