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Open AccessArticle

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

by Danilo Pena 1,*,†,‡, Carlos Lima 2,‡, Matheus Dória 2,‡, Luan Pena 1,‡, Allan Martins 1,‡ and Vicente Sousa 2,‡
1
Department of Electrical Engineering, Federal University of Rio Grande do Norte, 59078-970 Natal, Brazil
2
Department of Communications Engineering, Federal University of Rio Grande do Norte, 59078-970 Natal, Brazil
*
Author to whom correspondence should be addressed.
Current address: DEE-CT-UFRN, Campus Universitario, Lagoa Nova, 59078-970 Natal, Brazil.
These authors contributed equally to this work.
Sensors 2019, 19(12), 2827; https://doi.org/10.3390/s19122827
Received: 5 April 2019 / Revised: 23 May 2019 / Accepted: 29 May 2019 / Published: 25 June 2019
(This article belongs to the Section Intelligent Sensors)
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, α -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 α -stable model has the best fit for all tested scenarios. View Full-Text
Keywords: noise estimation; non-Gaussian noise; maximum likelihood; acoustic channel noise estimation; non-Gaussian noise; maximum likelihood; acoustic channel
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Pena, D.; Lima, C.; Dória, M.; Pena, L.; Martins, A.; Sousa, V. Acoustic Impulsive Noise Based on Non-Gaussian Models: An Experimental Evaluation. Sensors 2019, 19, 2827.

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