Innovation science and technologiy Ҷилди 2 № 4 (2026)

MATHEMATICAL MODELS AND ALGORITHMS FOR PROCESSING NOISE DATA

Jovlieva, Dilnoz

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Аннотатсия

This article is devoted to the analysis of mathematical models and algorithms for processing noisy data in moderninformation systems. The study examines the main approaches used to increase the signal-to-noise ratio, improve dataquality, and filter out erroneous data. The Results and Discussion section presents optimal models for various types ofnoise and their performance indicators in tabular form. The study highlights the importance of modern mathematical toolsin processing noisy data and their potential for practical applications.

noisy data, mathematical models, signal processing, adaptive filters, statistical methods, machine learning, noise filtering.

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Иқтибос гирифтан

APA 7 
Jovlieva, Dilnoz (2026). MATHEMATICAL MODELS AND ALGORITHMS FOR PROCESSING NOISE DATA. Innovation science and technologiy, 2(4).
GOST R 7.0.5 
Jovlieva, Dilnoz MATHEMATICAL MODELS AND ALGORITHMS FOR PROCESSING NOISE DATA // Innovation science and technologiy. 2026. Т. 2. № 4.
BibTeX 
@article{dilnoz2026,
  author  = {Jovlieva, Dilnoz},
  title   = {MATHEMATICAL MODELS AND ALGORITHMS FOR PROCESSING NOISE DATA},
  journal = {Innovation science and technologiy},
  year    = {2026},
  volume  = {2},
  number  = {4}
}
RIS 
TY  - JOUR
AU  - Jovlieva, Dilnoz
TI  - MATHEMATICAL MODELS AND ALGORITHMS FOR PROCESSING NOISE DATA
JO  - Innovation science and technologiy
PY  - 2026
VL  - 2
IS  - 4
ER  -