MATHEMATICAL MODELS AND ALGORITHMS FOR PROCESSING NOISE DATA
DOI:
https://doi.org/10.5281/zenodo.19465386Keywords:
noisy data, mathematical models, signal processing, adaptive filters, statistical methods, machine learning, noise filtering.Abstract
This article is devoted to the analysis of mathematical models and algorithms for processing noisy data in modern
information systems. The study examines the main approaches used to increase the signal-to-noise ratio, improve data
quality, and filter out erroneous data. The Results and Discussion section presents optimal models for various types of
noise and their performance indicators in tabular form. The study highlights the importance of modern mathematical tools
in processing noisy data and their potential for practical applications.
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