Fixed-time synchronization of delayed memristor-based recurrent neural networks

Research Paper

DOI: 10.1007/s11432-016-0555-2

Cite this article as:
Cao, J. & Li, R. Sci. China Inf. Sci. (2017) 60: 032201. doi:10.1007/s11432-016-0555-2


This paper focuses on the fixed-time synchronization control methodology for a class of delayed memristor-based recurrent neural networks. Based on Lyapunov functionals, analytical techniques, and together with novel control algorithms, sufficient conditions are established to achieve fixed-time synchronization of the master and slave memristive systems. Moreover, the settling time of fixed-time synchronization is estimated, which can be adjusted to desired values regardless of the initial conditions. Finally, the corresponding simulation results are included to show the effectiveness of the proposed methodology derived in this paper.


memristor fixed-time synchronization nonlinear control master-slave systems time delays 

Copyright information

© Science China Press and Springer-Verlag Berlin Heidelberg 2017

Authors and Affiliations

  1. 1.School of Mathematics, and Research Center for Complex Systems and Network SciencesSoutheast UniversityNanjingChina

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