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Acoustic Impulsive Noise Based on Non-Gaussian Models: An Experimental Evaluation

In general, acoustic channels are not Gaussian distributed neither are second-order stationary. Considering them for signal processing methods designed for Gaussian assumptions is inadequate, consequently yielding in poor performance of such methods. This paper presents an analysis for audio signal...

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Detalles Bibliográficos
Autores principales: Pena, Danilo, Lima, Carlos, Dória, Matheus, Pena, Luan, Martins, Allan, Sousa, Vicente
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6631147/
https://www.ncbi.nlm.nih.gov/pubmed/31242554
http://dx.doi.org/10.3390/s19122827
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author Pena, Danilo
Lima, Carlos
Dória, Matheus
Pena, Luan
Martins, Allan
Sousa, Vicente
author_facet Pena, Danilo
Lima, Carlos
Dória, Matheus
Pena, Luan
Martins, Allan
Sousa, Vicente
author_sort Pena, Danilo
collection PubMed
description In general, acoustic channels are not Gaussian distributed neither are second-order stationary. Considering them for signal processing methods designed for Gaussian assumptions is inadequate, consequently yielding in poor performance of such methods. This paper presents an analysis for audio signal corrupted by impulsive noise using non-Gaussian models. Audio samples are compared to the Gaussian, [Formula: see text]-stable and Gaussian mixture models, evaluating the fitting by graphical and numerical methods. We discuss fitting properties as the window length and the overlap, finally concluding that the [Formula: see text]-stable model has the best fit for all tested scenarios.
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spelling pubmed-66311472019-08-19 Acoustic Impulsive Noise Based on Non-Gaussian Models: An Experimental Evaluation Pena, Danilo Lima, Carlos Dória, Matheus Pena, Luan Martins, Allan Sousa, Vicente Sensors (Basel) Article In general, acoustic channels are not Gaussian distributed neither are second-order stationary. Considering them for signal processing methods designed for Gaussian assumptions is inadequate, consequently yielding in poor performance of such methods. This paper presents an analysis for audio signal corrupted by impulsive noise using non-Gaussian models. Audio samples are compared to the Gaussian, [Formula: see text]-stable and Gaussian mixture models, evaluating the fitting by graphical and numerical methods. We discuss fitting properties as the window length and the overlap, finally concluding that the [Formula: see text]-stable model has the best fit for all tested scenarios. MDPI 2019-06-25 /pmc/articles/PMC6631147/ /pubmed/31242554 http://dx.doi.org/10.3390/s19122827 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Pena, Danilo
Lima, Carlos
Dória, Matheus
Pena, Luan
Martins, Allan
Sousa, Vicente
Acoustic Impulsive Noise Based on Non-Gaussian Models: An Experimental Evaluation
title Acoustic Impulsive Noise Based on Non-Gaussian Models: An Experimental Evaluation
title_full Acoustic Impulsive Noise Based on Non-Gaussian Models: An Experimental Evaluation
title_fullStr Acoustic Impulsive Noise Based on Non-Gaussian Models: An Experimental Evaluation
title_full_unstemmed Acoustic Impulsive Noise Based on Non-Gaussian Models: An Experimental Evaluation
title_short Acoustic Impulsive Noise Based on Non-Gaussian Models: An Experimental Evaluation
title_sort acoustic impulsive noise based on non-gaussian models: an experimental evaluation
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6631147/
https://www.ncbi.nlm.nih.gov/pubmed/31242554
http://dx.doi.org/10.3390/s19122827
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