期刊
NEUROCOMPUTING
卷 159, 期 -, 页码 50-57出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.neucom.2015.02.031
关键词
Synchronization control; Neural networks; Brownian motion; Multiple time delays; LMI approach
资金
- Specialized Research Fund for the Doctoral Program of Higher Education [20120075120009]
- Natural Science Foundation of Shanghai [15ZR1401800, 12ZR1440200]
- Research Projects of Science and Technology of Hubei Province [Q20141305]
This paper deals with the synchronization problem for multiple time-varying delayed neural networks with the noise of Brownian motion. When the neural networks are affected by multiple time-varying delays, it is hard to deal with the synchronization for a large number of interconnected neuron units in such networks. In order to solve this problem which associates with complicated mathematic computing, a novel method is proposed to design the controller that guarantees the error system to be stable. Moreover, by using the Lyapunov-Krasovskii functional (LKF) method, stochastic analysis technique and matrix theory, a sufficient condition based on linear matrix inequality is obtained, thus the drive system can synchronize the response system. Finally, a numerical example is provided to demonstrate the effectiveness of the proposed synchronization schemes. (C) 2015 Elsevier B.V. All rights reserved.
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