Source separation in strong noisy mixtures: A study of wavelet de-noising pre-processing

A. Paraschiv-Ionescu; C. Jutten; K. Aminian; B. Najafi; P. Robert

doi:10.1109/ICASSP.2002.5744943

Source separation in strong noisy mixtures: A study of wavelet de-noising pre-processing

A. Paraschiv-Ionescu
, C. Jutten
, K. Aminian
, B. Najafi
, P. Robert

Research output: Contribution to journal › Article › peer-review

22 Scopus citations

Abstract

This paper addresses the source separation in strong noisy mixtures by wavelet de-noising processing. Experiments include the cases of white/correlated Gaussian and non-Gaussian noise, which correspond to various applications. The performance of BSS/ICA algorithms after wavelet de-noising is quantitatively investigated, and points out the efficiency of the method.

Original language	English (US)
Pages (from-to)	1681-1684
Number of pages	4
Journal	ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume	2
DOIs	https://doi.org/10.1109/ICASSP.2002.5744943
State	Published - 2002
Externally published	Yes

ASJC Scopus subject areas

Software
Signal Processing
Electrical and Electronic Engineering

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10.1109/ICASSP.2002.5744943

Cite this

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abstract = "This paper addresses the source separation in strong noisy mixtures by wavelet de-noising processing. Experiments include the cases of white/correlated Gaussian and non-Gaussian noise, which correspond to various applications. The performance of BSS/ICA algorithms after wavelet de-noising is quantitatively investigated, and points out the efficiency of the method.",

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AU - Robert, P.

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AB - This paper addresses the source separation in strong noisy mixtures by wavelet de-noising processing. Experiments include the cases of white/correlated Gaussian and non-Gaussian noise, which correspond to various applications. The performance of BSS/ICA algorithms after wavelet de-noising is quantitatively investigated, and points out the efficiency of the method.

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Source separation in strong noisy mixtures: A study of wavelet de-noising pre-processing

Abstract

ASJC Scopus subject areas

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