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The question of the optimum choice of weights in a weighted voting procedure used to improve information reliability is considered. The difficulty encountered in adjusting the weights by a classical perception is noted. An algorithm of perceptron-type adaptation which is capable of operating in both taught and self-taught modes is proposed. Its efficiency is demonstrated at both a theoretical and an experimental level.