Journal
NONLINEAR DYNAMICS
Volume 79, Issue 1, Pages 485-500Publisher
SPRINGER
DOI: 10.1007/s11071-014-1681-x
Keywords
Reaction-diffusion neural network; Stochastic sampled-data control; Synchronization; Linear matrix inequality
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Funding
- NBHM
- National Natural Science Foundation of China [61374080]
- Natural Science Foundation of Zhejiang Province [LY12F03010]
- Natural Science Foundation of Ningbo [2012A610032]
- Priority Academic Program Development of Jiangsu Higher Education Institutions
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This paper discusses the synchronization problem for a class of reaction diffusion neural networks with Dirichlet boundary conditions. Unlike other studies, a sampled-data controller with stochastic sampling is designed in order to synchronize the concerned neural networks with reaction diffusion terms and time-varying delays, where m sampling periods are considered whose occurrence probabilities are given constants and satisfy the Bernoulli distribution. A novel discontinuous Lyapunov-Krasovskii functional with triple integral terms is introduced based on the extended Wirtinger's inequality. Using Jensen's inequality and reciprocally convex technique in deriving the upper bound for the derivative of the Lyapunov-Krasovskii functional, some new synchronization criteria are obtained in terms of linear matrix inequalities. Numerical examples are provided in order to show the effectiveness of the proposed theoretical results.
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