Construction of a Logical-Algebraic Corrector to Increase the Adaptive Properties of the ΣΠ-Neuron

In this paper, we consider the problem of constructing a correction algorithm with aim increasing adaptive properties ΣΠ-neuron, relying solely on structure ΣΠ-neuron itself. To build corrector, logical-algebraic method data analysis is used. Comparison advantages neural network approach and suggests that combined to organization improves its efficiency allows one set rules reveal hidden patterns in given subject area, thus improving quality recognition system.