72294

Автор(ов): 

3

Параметры публикации
Тип публикации: 
Статья в журнале/сборнике
Название: 
Comparison of Information Criteria for Detection of Useful Signals in Noisy Environments
DOI: 
10.3390/s23042133
Наименование источника: 
Sensors
Обозначение и номер тома: 
23(4)
Город: 
Basel, Швейцария
Издательство: 
MDPI AG
Год издания: 
2023
Страницы: 
https://www.mdpi.com/1424-8220/23/4/2133
Аннотация
This paper considers the appearance of indications of useful acoustic signals in the signal/noise mixture. Various information characteristics (information entropy, Jensen–Shannon divergence, spectral information divergence and statistical complexity) are investigated in the context of solving this problem. Both time and frequency domains are studied for the calculation of information entropy. The effectiveness of statistical complexity is shown in comparison with other information metrics for different signal-to-noise ratios. Two different approaches for statistical complexity calculations are also compared. In addition, analytical formulas for complexity and disequilibrium are obtained using entropy variation in the case of signal spectral distribution. The connection between the statistical complexity criterion and the Neyman–Pearson approach for hypothesis testing is discussed. The effectiveness of the proposed approach is shown for different types of acoustic signals and noise models, including colored noises, and different signal-to-noise ratios, especially when the estimation of additional noise characteristics is impossible.
Библиографическая ссылка: 
Галяев А.А., Лысенко П.В., Берлин Л.М. Comparison of Information Criteria for Detection of Useful Signals in Noisy Environments // Sensors. 2023. 23(4). С. https://www.mdpi.com/1424-8220/23/4/2133.