78333

Автор(ов): 

4

Параметры публикации
Тип публикации: 
Статья в журнале/сборнике
Название: 
A New Spectral Measure of Complexity and Its Capabilities for Detecting Signals in Noise
ISBN/ISSN: 
1064-5624
DOI: 
10.1134/S1064562424702235
Наименование источника: 
Doklady Mathematics
Город: 
Москва
Издательство: 
Pleiades Publishing, Ltd.
Год издания: 
2024
Страницы: 
1-8 https://link.springer.com/article/10.1134/S1064562424702235#citeas
Аннотация
This article is devoted to the improvement of signal recognition methods based on information characteristics of the spectrum. A discrete function of the normalized ordered spectrum is established for a single window function included in the discrete Fourier transform. Lemmas on estimates of entropy, imbalance, and statistical complexity in processing a time series of independent Gaussian variables are proved. New concepts of one- and two-dimensional spectral complexities are proposed. The theoretical results were verified by numerical experiments, which confirmed the effectiveness of the new information characteristic for detecting a signal mixed with white noise at low signal-to-noise ratios.
Библиографическая ссылка: 
Галяев А.А., Бабиков В.Г., Лысенко П.В., Берлин Л.М. A New Spectral Measure of Complexity and Its Capabilities for Detecting Signals in Noise / Doklady Mathematics. М.: Pleiades Publishing, Ltd., 2024. С. 1-8 https://link.springer.com/article/10.1134/S1064562424702235#citeas.