Isolation of a periodic component by singular wavelet decomposition

In this paper, we propose to use a discrete wavelet transform with a singular wavelet to isolate the periodic component from the signal. Traditionally, it is assumed that the validity condition must be met for a basic wavelet (the average value of the wavelet is zero). For singular wavelets, the val...

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Main Authors: V. M. Romanchak, M. A. Hundzina
Format: Article
Language:English
Published: Belarusian National Technical University 2020-09-01
Series:Системный анализ и прикладная информатика
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Online Access:https://sapi.bntu.by/jour/article/view/477
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author V. M. Romanchak
M. A. Hundzina
author_facet V. M. Romanchak
M. A. Hundzina
author_sort V. M. Romanchak
collection DOAJ
description In this paper, we propose to use a discrete wavelet transform with a singular wavelet to isolate the periodic component from the signal. Traditionally, it is assumed that the validity condition must be met for a basic wavelet (the average value of the wavelet is zero). For singular wavelets, the validity condition is not met. As a singular wavelet, you can use the Delta-shaped functions, which are involved in the estimates of Parzen-Rosenblatt, Nadaraya-Watson. Using singular value of a wavelet is determined by the discrete wavelet transform. This transformation was studied earlier for the continuous case. Theoretical estimates of the convergence rate of the sum of wavelet transformations were obtained; various variants were proposed and a theoretical justification was given for the use of the singular wavelet method; sufficient conditions for uniform convergence of the sum of wavelet transformations were formulated. It is shown that the wavelet transform can be used to solve the problem of nonparametric approximation of the function. Singular wavelet decomposition is a new method and there are currently no examples of its application to solving applied problems. This paper analyzes the possibilities of the singular wavelet method. It is assumed that in some cases a slow and fast component can be distinguished from the signal, and this hypothesis is confirmed by the numerical solution of the real problem. A similar analysis is performed using a parametric regression equation, which allows you to select the periodic component of the signal. Comparison of the calculation results confirms that nonparametric approximation based on singular wavelets and the application of parametric regression can lead to similar results.
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spelling doaj-art-d78944d6aa9b4c52875abd5bc59685032025-02-03T11:37:39ZengBelarusian National Technical UniversityСистемный анализ и прикладная информатика2309-49232414-04812020-09-01034810.21122/2309-4923-2020-3-4-8360Isolation of a periodic component by singular wavelet decompositionV. M. Romanchak0M. A. Hundzina1Belarusian National Technical UniversityBelarusian National Technical UniversityIn this paper, we propose to use a discrete wavelet transform with a singular wavelet to isolate the periodic component from the signal. Traditionally, it is assumed that the validity condition must be met for a basic wavelet (the average value of the wavelet is zero). For singular wavelets, the validity condition is not met. As a singular wavelet, you can use the Delta-shaped functions, which are involved in the estimates of Parzen-Rosenblatt, Nadaraya-Watson. Using singular value of a wavelet is determined by the discrete wavelet transform. This transformation was studied earlier for the continuous case. Theoretical estimates of the convergence rate of the sum of wavelet transformations were obtained; various variants were proposed and a theoretical justification was given for the use of the singular wavelet method; sufficient conditions for uniform convergence of the sum of wavelet transformations were formulated. It is shown that the wavelet transform can be used to solve the problem of nonparametric approximation of the function. Singular wavelet decomposition is a new method and there are currently no examples of its application to solving applied problems. This paper analyzes the possibilities of the singular wavelet method. It is assumed that in some cases a slow and fast component can be distinguished from the signal, and this hypothesis is confirmed by the numerical solution of the real problem. A similar analysis is performed using a parametric regression equation, which allows you to select the periodic component of the signal. Comparison of the calculation results confirms that nonparametric approximation based on singular wavelets and the application of parametric regression can lead to similar results.https://sapi.bntu.by/jour/article/view/477waveletwavelet transformparsen window–rosenblattnonparametric approximationnuclear assessment nadaraya-watson
spellingShingle V. M. Romanchak
M. A. Hundzina
Isolation of a periodic component by singular wavelet decomposition
Системный анализ и прикладная информатика
wavelet
wavelet transform
parsen window–rosenblatt
nonparametric approximation
nuclear assessment nadaraya-watson
title Isolation of a periodic component by singular wavelet decomposition
title_full Isolation of a periodic component by singular wavelet decomposition
title_fullStr Isolation of a periodic component by singular wavelet decomposition
title_full_unstemmed Isolation of a periodic component by singular wavelet decomposition
title_short Isolation of a periodic component by singular wavelet decomposition
title_sort isolation of a periodic component by singular wavelet decomposition
topic wavelet
wavelet transform
parsen window–rosenblatt
nonparametric approximation
nuclear assessment nadaraya-watson
url https://sapi.bntu.by/jour/article/view/477
work_keys_str_mv AT vmromanchak isolationofaperiodiccomponentbysingularwaveletdecomposition
AT mahundzina isolationofaperiodiccomponentbysingularwaveletdecomposition