Impulsive stabilization of delayed neural networks with and without uncertainty

Many dynamic systems in physics, chemistry, biology, engineering, and information science have impulsive dynamical behaviours due to abrupt jumps at certain instants during the dynamical process, and these complex dynamic behaviours can be modelled by impulsive differential systems. This paper formulates and studies the impulsive stabilization of the Hopfield-type delayed neural networks with and without uncertainty. Several criteria guaranteeing stabilization of such systems are established by employing Lyapunov-like stability theorem, linear matrix inequality approach, and other inequality techniques. A simple approach to the design of an impulsive controller is then presented. Two numerical examples are given for illustration of the theoretical results. Copyright © 2007 John Wiley & Sons, Ltd.

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