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Neurocomputing 159 (2015) 50–57
Contents lists available at ScienceDirect
Neurocomputing
journal homepage: /locate/neucom
Brief Paper
A novel scheme for synchronization control of stochastic neural
networks with multiple time-varying delays $
Xianghui Zhou a,b, Wuneng Zhou a,c,n, Jun Yang a, Jie Hu b
a College of Information Sciences and Technology, Donghua University, Shanghai 200051, China
b Freshman Education Department, Yangtze University, Jing Zhou 434023, China
c Engineering Research Center of Digitized Textile Fashion Technology, Ministry of Education, Donghua University, Shanghai 201620, China
a r t i c l e i n f o a b s t r a c t
Article history: This paper deals with the synchronization problem for multiple time-varying delayed neural networks
Received 18 October 2014 with the noise of Brownian motion. When the neural networks are affected by multiple time-varying
Received in revised form delays, it is hard to deal with the synchronization for a large number of interconnected neuron units in
29 December 2014
such networks. In order to solve this problem which associates with complicated mathematic
Accepted 9 February 2015
computing, a novel method is proposed to design the controller that guarantees the error system to
Communicated by H. Zhang
Available online 24 February 2015 be stable. Moreover, by using the Lyapunov–Krasovskii functional (LKF) method, stochastic a
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