Improved identification of subscribers using a perceptron model
Markovskiy O.P., Mazur R.F., Said Reza Makh Mali
The paper deals with offers how to improve the using of neuronet technologies for remote multi-user systems subscribers identification. Usage of the perceptron model as the ambiguous reversible functional transformation allows to accelerate the identification process based on “zero knowledge” concepts. New ways of speeding up
the perceptron model are exposed. What the article brings out is the new calculation scheme. Its efficiency is discovered both analytically and experimentally in order to grade up the identification performance.