Exponential synchronization of neural networks with time-varying mixed delays and sampled-data

Authors:
Chuan-Ke Zhang;Yong He;Min Wu
Affiliations:
School of Information Science and Engineering, Central South University, Changsha 410083, PR China;School of Information Science and Engineering, Central South University, Changsha 410083, PR China;School of Information Science and Engineering, Central South University, Changsha 410083, PR China
Venue:
Neurocomputing
Year:
2010

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Abstract

This paper investigates the problem of exponential synchronization for neural networks with mixed delays using sampled-data feedback control. Lyapunov-Krasovskii functional combining with the input delay approach as well as the improved free-weighting matrix approach are employed to derive several sufficient criteria ensuring the delayed neural networks to be exponentially synchronous. The conditions obtained are dependent not only on the maximum sampling interval but also on the exponential synchronization rate. A numerical example is given to demonstrate the usefulness and merits of the proposed scheme.