Formation of a Model for End-to-End Data Mining Technology for Construction and Processing of RAW Big Data for Computer Vision Systems

Abstract

This article presents a comparative analysis of dynamic systems with full memory, which pass through all States in a continuous manner without loss and are represented by the convolution integral, Markov systems with a complete lack of memory and ereditar systems, occupying an intermediate place between Markov and simple systems with full memory for use in the production and processing of dynamic images. Possibility of use of the simplest wavelet transforms in the formation of hereditary models for the algorithms to handle dynamic images with the parent wavelet–function is a step function Haar (integration of the first order) that can be used in the generalized spectral analysis of dynamic images.