MODIFIED FUNCTION PROJECTIVE SYNCHRONIZATION OF CHAOTIC NEURAL NETWORKS WITH DELAYS BASED ON OBSERVER

Abstract

This paper deals with a new type of synchronization scheme for chaotic neural networks with delays, called modified function projective synchronization, in which chaotic neural networks synchronize up to a scaling function matrix. Based on the nonlinear state observer, a control scheme is derived through the placement technique by designing a state-observer of the derived system to synchronize chaotic neural networks up to a scaling function matrix. This technique, capable of adjusting the scaling function factor arbitrarily for the value of scaling function factor, has no effect on the controllability of error system. That overcomes some limitation in earlier literature. A chaotic cellular neural network and a chaotic Hopfield neural model are used as numerical examples to demonstrate the effectiveness of the proposed synchronization technique.