The neural network model synthesis based on the fractal analysis

Abstract

The problem of neural network model synthesis using the fractal analysis is addressed in the paper. The set of indicators characterizing the data sample properties from the unified position based on the fractal analysis principles is proposed. The methods of sample fractal dimension determining are proposed. These methods and indicators can be used to solve the problem of data dimensionality reduction. The set of indicators characterizing properties of neural network model is proposed. These indicators can be used in the process of neural network synthesis for the weights set contrasting, also as to find and remove the non-informative features and non-informative connections from the neural network model. The developed indicators and methods are implemented in software and studied at practical problem solving.