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Impulsive synchronization results are presented for discrete-time neural networks with delay, using linear matrix inequality and vector Lyapunov function techniques. The synchronizing impulses are assumed to contain non-delayed, as well as delayed terms. An example is given to illustrate the effectiveness of the results.
In ANN terminology, the synaptic connections are the weights of the neural networks and can be seen as an interaction between neurons. In this paper, we consider two simple neurons which have both self-coupling and non-invertible activation functions. Our studies on these interactions lead to different dynamical behaviors of the network. We show that they can be used as a means of chaos generation...
A number of methods have been proposed for synchronizing chaotic systems. The most widely used methods are continuous synchronization schemes. In a continuous synchronization scheme, chaotic systems are coupled to each other continuously such that synchronization errors converge to zero. In this paper, chaos synchronization in coupled discrete-time dynamical systems is presented. Especially, practical...
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