Synchronization Control for Stochastic Neural Networks with Mixed Time-Varying Delays

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 glo...

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Detalles Bibliográficos
Autores principales: Zhu, Qing, Song, Aiguo, Fei, Shumin, Yang, Yuequan, Cao, Zhiqiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2014
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4106077/
https://www.ncbi.nlm.nih.gov/pubmed/25110747
http://dx.doi.org/10.1155/2014/840185
Descripción
Sumario: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.

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