Radiotekhnika
Publishing house Radiotekhnika

"Publishing house Radiotekhnika":
scientific and technical literature.
Books and journals of publishing houses: IPRZHR, RS-PRESS, SCIENCE-PRESS


Тел.: +7 (495) 625-9241

 

Neural networks and discriminant functions

Keywords:

B. V. Khakimov – Dr.Sc. (Econom.), Advisor of the Federation Council. E-mail: bvhakimov@yandex.ru
D. A. Tarkhov – Dr.Sc. (Eng.), Professor, St. Petersburg State Polytechnical University. E-mail: dtarkhov@gmail.com <> I. M. Mikheev – D.Sc. (Phys.-Math.), Рrofessor, Moscow State Technical University of Civil Aviation. E-mail: igormikheev@mail.ru


The article deals with a geometrical interpretation of the neuron’s models. The interpretation shows some discriminant functions which divides inputs variable‘s area into parts with objects in question. The linear discriminant function corresponds to the most of known neuron’s models. A piecewise linear discriminant function corresponds to neural networks, a piecewise polynomial one – to the group method of data handling (GMDH). The neuron’s spline-model is a nonlinear discriminant function which is complicated and to a first approximation can be realized by 3- or 4-layer network of the known neurons. The workabilities of discriminant functions are demonstrated as an adequate and visual instrument of neuron models’ and neural networks’ analysis, of working on theoretical tasks, improvement of synthesis and setting of neural networks’ algorithms.
References:

  1. Ivaxnenko A.G. Induktivny'j metod samoorganizaczii modelej slozhny'x sistem. Kiev: Naukova dumka. 1982.
  2. Xakimov B.V., Mixeev I.M. Nelinejnaya model' nejrona – mnogomerny'j splajn // Nejrokomp'yutery': razrabotka, primenenie. 2012. № 7. S. 36–40.
  3. Tarxov D.A. Nejronny'e seti: modeli i algoritmy'. M.: Radiotexnika. 2005. 

© Издательство «РАДИОТЕХНИКА», 2004-2017            Тел.: (495) 625-9241                   Designed by [SWAP]Studio