Neural Computing and Applications

, Volume 19, Issue 4, pp 543–548

Algebraic condition of synchronization for multiple time-delayed chaotic Hopfield neural networks

Original Article

DOI: 10.1007/s00521-009-0306-7

Cite this article as:
He, H. & Tu, J. Neural Comput & Applic (2010) 19: 543. doi:10.1007/s00521-009-0306-7


In this paper, an easy and efficient method is brought forward to design the feedback control for the synchronization of two multiple time-delayed chaotic Hopfield neural networks, whose activation functions and delayed activation functions can have different forms of mapping. Without many complex restrictions and Lyapunov analytic process, the feedback control is given based on the M-matrix theory, the system parameters and the feedback section coefficients. All the results are simulated by Matlab and Simulink, which shows the simplicity and validity of the control. As shown in the simulation results, the error systems converge to zero rapidly.


SynchronizationChaosHopfield neural networkTime delaysAlgebraic condition

Copyright information

© Springer-Verlag London Limited 2009

Authors and Affiliations

  1. 1.College of ScienceNaval University of EngineeringWuhanChina