Designing cellular neural networks for the evaluation of local Boolean functions

Describes general methods for designing a cellular neural network implementing an arbitrary Boolean function defined on the r-neighborhood. This is achieved by operating the network with time-variant templates as a cellular automaton that processes only binary inputs. These methods are suitable for solving local tasks. As an example, testing minimal distances is discussed.<
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