Journal
INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS
Volume 9, Issue 1, Pages 104-111Publisher
INST CONTROL ROBOTICS & SYSTEMS, KOREAN INST ELECTRICAL ENGINEERS
DOI: 10.1007/s12555-011-0113-7
Keywords
Chaos synchronization; chaotic neural network; logistic map; stabilization
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In this paper, we consider a Hopfield like Chaotic Neural Networks which have both self-coupling and non-invertible activation functions. We show that the interactions between neurons can be used as a means of chaos generation or suppression to neuron's outputs when more adaptability or stability is required. Furthermore, a new set of sufficient conditions based on coupling weights is proposed so that the synchronization of all neuron's outputs with each other is guaranteed, when all neuron's have identical activation functions. Finally, the effectiveness of the proposed approach is evaluated by performing simulations on three illustrative examples.
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