Abstract
Genetic algorithms are applied to design multilayer discrete-time cellular neural networks for image processing tasks, To this end not only the templates of the different layers will be optimized, but also the network structure itself, that is, number of layers and iterations per layer. As a difference with traditional strategies, both the definition of the optimum network size and the template optimization are done simultaneously.
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