Abstract
An effective neural network algorithm of the perceptron type is proposed. The
algorithm allows us to identify strongly distorted input vector reliably. It is
shown that its reliability and processing speed are orders of magnitude higher
than that of full connected neural networks. The processing speed of our
algorithm exceeds the one of the stack fast-access retrieval algorithm that is
modified for working when there are noises in the input channel.
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