Part 2. Special Issues in Intellectual Systems Theory

On reducing the nonlinear depth of multidimensional convolutional neural schemes

A. V. Khapkin

Lomonosov Moscow State University, Faculty of Mechanics and Mathematics

Abstract: The paper considers multidimensional convolutional schemes in the McCulloch-Pitts basis. It is shown that the considered schemes can be implemented by a scheme from the a priori and dynamic parts, in which the calculations in the a priori part are independent of the input data. In this case, the a priori and dynamic parts have a nonlinear depth equal to $ 2 $.

Keywords: convolutional neural network, neural scheme, nonlinear complexity, McCulloch-Pitts model.