Title :
Impulsive Synchronization of Typical Hopfield Neural Networks
Author :
Qunli, Zhang ; Guanjun, Jia
Author_Institution :
Heze Univ., Heze
Abstract :
This paper is mainly concerned with the issues of impulsive control for synchronization of Hopfield neural networks. By using stability theory of impulsive dynamical systems, some simple yet generic criteria are derived ensuring the robust synchronization of Hopfield neural networks. Moreover, the approaches developed here further extend the techniques presented in recent literature. To this end, the theoretical results are applied to a typical delayed chaotic Hopfield neural networks and an autonomous chaotic Hopfield neural networks, and numerical simulations also demonstrate the effectiveness and feasibility of the proposed technique.
Keywords :
Hopfield neural nets; Lyapunov methods; differential equations; stability; synchronisation; Lyapunov stability; chaotic Hopfield neural networks; differential equations; impulsive control; impulsive dynamical systems; impulsive synchronization; Cellular neural networks; Chaos; Control systems; Differential equations; Hopfield neural networks; Master-slave; Neural networks; Numerical simulation; Recurrent neural networks; Robust stability; Chaos synchronization; Gronwall Inequality; Hopfield neural networks; Impulsive control; Lyapunov stability;
Conference_Titel :
Control Conference, 2007. CCC 2007. Chinese
Conference_Location :
Hunan
Print_ISBN :
978-7-81124-055-9
Electronic_ISBN :
978-7-900719-22-5
DOI :
10.1109/CHICC.2006.4346890