Multivariate Decomposition of Acoustic Signals in Dispersive Channels

We present a signal decomposition procedure, which separates modes into individual components while preserving their integrity, in effort to tackle the challenges related to the characterization of modes in an acoustic dispersive environment. With this approach, each mode can be analyzed and process...

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Autores principales:	Miloš Brajović, Isidora Stanković, Jonatan Lerga, Cornel Ioana, Eftim Zdravevski, Miloš Daković
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	concentration measures dispersive channels multivariate signals non-stationary signals multicomponent signal decomposition Mathematics QA1-939
Acceso en línea:	https://doaj.org/article/76910dbdc91f48b391486fa2ec60bc63
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spelling	oai:doaj.org-article:76910dbdc91f48b391486fa2ec60bc632021-11-11T18:19:56ZMultivariate Decomposition of Acoustic Signals in Dispersive Channels10.3390/math92127962227-7390https://doaj.org/article/76910dbdc91f48b391486fa2ec60bc632021-11-01T00:00:00Zhttps://www.mdpi.com/2227-7390/9/21/2796https://doaj.org/toc/2227-7390We present a signal decomposition procedure, which separates modes into individual components while preserving their integrity, in effort to tackle the challenges related to the characterization of modes in an acoustic dispersive environment. With this approach, each mode can be analyzed and processed individually, which carries opportunities for new insights into their characterization possibilities. The proposed methodology is based on the eigenanalysis of the autocorrelation matrix of the analyzed signal. When eigenvectors of this matrix are properly linearly combined, each signal component can be separately reconstructed. A proper linear combination is determined based on the minimization of concentration measures calculated exploiting time-frequency representations. In this paper, we engage a steepest-descent-like algorithm for the minimization process. Numerical results support the theory and indicate the applicability of the proposed methodology in the decomposition of acoustic signals in dispersive channels.Miloš BrajovićIsidora StankovićJonatan LergaCornel IoanaEftim ZdravevskiMiloš DakovićMDPI AGarticleconcentration measuresdispersive channelsmultivariate signalsnon-stationary signalsmulticomponent signal decompositionMathematicsQA1-939ENMathematics, Vol 9, Iss 2796, p 2796 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	concentration measures dispersive channels multivariate signals non-stationary signals multicomponent signal decomposition Mathematics QA1-939
spellingShingle	concentration measures dispersive channels multivariate signals non-stationary signals multicomponent signal decomposition Mathematics QA1-939 Miloš Brajović Isidora Stanković Jonatan Lerga Cornel Ioana Eftim Zdravevski Miloš Daković Multivariate Decomposition of Acoustic Signals in Dispersive Channels
description	We present a signal decomposition procedure, which separates modes into individual components while preserving their integrity, in effort to tackle the challenges related to the characterization of modes in an acoustic dispersive environment. With this approach, each mode can be analyzed and processed individually, which carries opportunities for new insights into their characterization possibilities. The proposed methodology is based on the eigenanalysis of the autocorrelation matrix of the analyzed signal. When eigenvectors of this matrix are properly linearly combined, each signal component can be separately reconstructed. A proper linear combination is determined based on the minimization of concentration measures calculated exploiting time-frequency representations. In this paper, we engage a steepest-descent-like algorithm for the minimization process. Numerical results support the theory and indicate the applicability of the proposed methodology in the decomposition of acoustic signals in dispersive channels.
format	article
author	Miloš Brajović Isidora Stanković Jonatan Lerga Cornel Ioana Eftim Zdravevski Miloš Daković
author_facet	Miloš Brajović Isidora Stanković Jonatan Lerga Cornel Ioana Eftim Zdravevski Miloš Daković
author_sort	Miloš Brajović
title	Multivariate Decomposition of Acoustic Signals in Dispersive Channels
title_short	Multivariate Decomposition of Acoustic Signals in Dispersive Channels
title_full	Multivariate Decomposition of Acoustic Signals in Dispersive Channels
title_fullStr	Multivariate Decomposition of Acoustic Signals in Dispersive Channels
title_full_unstemmed	Multivariate Decomposition of Acoustic Signals in Dispersive Channels
title_sort	multivariate decomposition of acoustic signals in dispersive channels
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/76910dbdc91f48b391486fa2ec60bc63
work_keys_str_mv	AT milosbrajovic multivariatedecompositionofacousticsignalsindispersivechannels AT isidorastankovic multivariatedecompositionofacousticsignalsindispersivechannels AT jonatanlerga multivariatedecompositionofacousticsignalsindispersivechannels AT cornelioana multivariatedecompositionofacousticsignalsindispersivechannels AT eftimzdravevski multivariatedecompositionofacousticsignalsindispersivechannels AT milosdakovic multivariatedecompositionofacousticsignalsindispersivechannels
_version_	1718431893378039808

Multivariate Decomposition of Acoustic Signals in Dispersive Channels

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