Розпізнавання рівня шуму фрактального броунівського руху

Abstract

This work focuses on developing a methodology for assessing the noise level of fractal Brownian motion using machine learning techniques, particularly a convolutional neural network. Input data comprise fractal Brownian motion realizations with varying degrees of noise, and neural network approaches are utilized for their recognition. The findings shed light on the efficacy and reliability of employing such machine learning methodologies in the domain of noise assessment within fractal systems.