title: Synchronization control for stochastic neural networks with mixed time-varying delays.
abstract: Synchronization control of stochastic neural networks with time-varying discrete and continuous delays has been investigated. A novel control scheme is proposed using the Lyapunov functional method and linear matrix inequality (LMI) approach. Sufficient conditions have been derived to ensure the global asymptotical mean-square stability for the error system, and thus the drive system synchronizes with the response system. Also, the control gain matrix can be obtained. With these effective methods, synchronization can be achieved. Simulation results are presented to show the effectiveness of the theoretical results.
authors.affiliation: School of Instrument Science, Southeast University, Nanjing 210096, China ; College of Information Engineering, Yangzhou University, Yangzhou 225009, China.
authors.forename: Qing
authors.initials: Q
authors.lastname: Zhu
authors.affiliation: School of Instrument Science, Southeast University, Nanjing 210096, China.
authors.forename: Aiguo
authors.initials: A
authors.lastname: Song
authors.affiliation: School of Automation, Southeast University, Nanjing 210096, China.
authors.forename: Shumin
authors.initials: S
authors.lastname: Fei
authors.affiliation: College of Information Engineering, Yangzhou University, Yangzhou 225009, China.
authors.forename: Yuequan
authors.initials: Y
authors.lastname: Yang
authors.affiliation: Institute of Automation, Chinese Academy of Science, Beijing 100190, China.
authors.forename: Zhiqiang
authors.initials: Z
authors.lastname: Cao
mesh_terms: D000465:Algorithms; D008962:Models, Theoretical; D016571:Neural Networks, Computer
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