Abstract
In this work we present a novel strategy for the simultaneous design and training of multilayer discrete-time cellular neural networks. This methodology is applied to the detection of surface-laid antipersonnel mines in infrared imaging. The procedure is based on the application of genetic algorithms for both network design and learning task.
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