Exponential synchronization for delayed recurrent neural networks via periodically intermittent control

Authors:
Jiuju Xing;Haijun Jiang;Cheng Hu
Affiliations:
College of Mathematics and System Sciences, Xinjiang University, Urumqi, 830046 Xinjiang, PR China;College of Mathematics and System Sciences, Xinjiang University, Urumqi, 830046 Xinjiang, PR China;College of Mathematics and System Sciences, Xinjiang University, Urumqi, 830046 Xinjiang, PR China
Venue:
Neurocomputing
Year:
2013

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Abstract

In this paper, the exponential synchronization for a class of delayed recurrent neural networks is investigated by virtue of intermittent control schemes. Based on p-norm and ~-norm, respectively, several new and useful synchronization criteria are derived by applying Lyapunov functional theory, mathematical induction and inequality technique. Particularly, some feasible regions of control parameters for each neuron are derived for the realization of exponential synchronization, which provides great convenience to the applications of the theoretical results. Finally, some numerical simulations are given to demonstrate the effectiveness of the proposed control methods.