Keywords: spectral analysis, signal digital processing, discrete spectrum, prony filtering, extremal filtering, fourier transform
Express method for determining the spectral composition of a signal based on extreme filtering
UDC 51-74
DOI: 10.26102/2310-6018/2022.37.2.027
To date, one of the most common systems are those based on the results of measurement experiments. The processing of experimental data is widely used in information-measuring systems, technical control and diagnostic systems as well as in automated control systems. Spectral methods are a powerful and most widely used tool for data processing and analysis. Spectral characteristics are employed extensively in engineering due to their high informative value and reversibility, which makes it possible to perform signal compression and restoration with high calculation accuracy. Questions of spectral signal analysis and descriptions of the main methods for spectrum extraction are examined. An express method for determining the spectral composition of a signal through extreme filtering is considered. The results of processing experimentally registered signals from the paper machine scanner are presented. A method for quick spectrum extraction through extreme filtering is described, which provides the means for analyzing the spectral composition of a signal with the aid of available software tools and obtain visual representations of a wide range of characteristics that help to compile a complete description of the signal under study. The results show the convergence with the minimization of computational effort and simplification of the algorithm. These factors enable the application of this method for quick analysis in technical systems.
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Keywords: spectral analysis, signal digital processing, discrete spectrum, prony filtering, extremal filtering, fourier transform
For citation: Myasnikova N.V., Lysova N.V. Express method for determining the spectral composition of a signal based on extreme filtering. Modeling, Optimization and Information Technology. 2022;10(2). URL: https://moitvivt.ru/ru/journal/pdf?id=1173 DOI: 10.26102/2310-6018/2022.37.2.027 (In Russ).
Received 11.05.2022
Revised 24.06.2022
Accepted 29.06.2022
Published 30.06.2022