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Wavelet Filtering of Signals without Using Model Functions

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Abstract

The effective wavelet filtering of real signals is impossible without determining their shape. The shape of a real signal is related to its wavelet spectrum. For shape analysis, a continuous color wavelet spectrogram of signal level is often used. The disadvantage of continuous wavelet spectrogram is the complexity of analyzing a blurry color image. A real signal with additive noise strongly distorts the spectrogram based on continuous wavelet analysis compared to a pure signal. Therefore, the identification of a real signal by using a continuous color wavelet spectrogram is difficult. To solve this problem, for the first time, a comparative analysis of spectrograms of signals and correlation matrices is carried out. The spectrograms of signals are obtained based on continuous wavelet transformation in the form of images with areas of different colors of variable intensity. Correlation matrices are computed by using mathematical functions of the coefficients of discrete wavelet spectra.

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Correspondence to Yurii Taranenko.

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Y. Taranenko, N. Rizun

The authors declare that they have no conflicts of interest.

This article does not contain any studies with human participants or animals performed by any of the authors.

The initial version of this paper in Russian is published in the journal “Izvestiya Vysshikh Uchebnykh Zavedenii. Radioelektronika,” ISSN 2307-6011 (Online), ISSN 0021-3470 (Print) on the link http://radio.kpi.ua/article/view/S0021347022020042 with DOI: https://doi.org/10.20535/S0021347022020042

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Translated from Izvestiya Vysshikh Uchebnykh Zavedenii. Radioelektronika, No. 2, pp. 110-125, February, 2022 https://doi.org/10.20535/S0021347022020042 .

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Taranenko, Y., Rizun, N. Wavelet Filtering of Signals without Using Model Functions. Radioelectron.Commun.Syst. 65, 96–109 (2022). https://doi.org/10.3103/S0735272722020042

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  • DOI: https://doi.org/10.3103/S0735272722020042

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