Removal of partially correlated noise to improve signal to noise ratio - a theoretical study

Research output: Chapter in Book/Conference proceeding with ISSN or ISBNConference contribution with ISSN or ISBNResearchpeer-review

Abstract

Time correlation and decorrelation are well established tools to improve the signal to noise ratio of a system, yet they are often poorly understood. When several unwanted signals are correlated they are much easier to remove from uncorrelated wanted signals than vice versa, where a much poorer improvement is possible. A case in point is the removal of wind noise from microphone signals. The situation is further compounded when one or other of the signals is only partially correlated, or different spectral content is differently correlated. This paper looks at the theoretical improvement in signal to noise ratio when either the signal or the noise are correlated to different degrees. Application to real microphone signals and noise is discussed.
Original languageEnglish
Title of host publicationProceedings of the 137th AES Convention
Place of PublicationLos Angelese
Pages0-0
Number of pages1
Publication statusPublished - 1 Oct 2014
EventProceedings of the 137th AES Convention - Los Angeles, CA, USA, 9-12 October 2014
Duration: 1 Oct 2014 → …

Conference

ConferenceProceedings of the 137th AES Convention
Period1/10/14 → …

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Microphones
Signal to noise ratio

Bibliographical note

© 2014 AES. All rights reserved.

Cite this

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title = "Removal of partially correlated noise to improve signal to noise ratio - a theoretical study",
abstract = "Time correlation and decorrelation are well established tools to improve the signal to noise ratio of a system, yet they are often poorly understood. When several unwanted signals are correlated they are much easier to remove from uncorrelated wanted signals than vice versa, where a much poorer improvement is possible. A case in point is the removal of wind noise from microphone signals. The situation is further compounded when one or other of the signals is only partially correlated, or different spectral content is differently correlated. This paper looks at the theoretical improvement in signal to noise ratio when either the signal or the noise are correlated to different degrees. Application to real microphone signals and noise is discussed.",
author = "Simon Busbridge and Christopher Garrett",
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year = "2014",
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booktitle = "Proceedings of the 137th AES Convention",

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Busbridge, S & Garrett, C 2014, Removal of partially correlated noise to improve signal to noise ratio - a theoretical study. in Proceedings of the 137th AES Convention. Los Angelese, pp. 0-0, Proceedings of the 137th AES Convention, 1/10/14.

Removal of partially correlated noise to improve signal to noise ratio - a theoretical study. / Busbridge, Simon; Garrett, Christopher.

Proceedings of the 137th AES Convention. Los Angelese, 2014. p. 0-0.

Research output: Chapter in Book/Conference proceeding with ISSN or ISBNConference contribution with ISSN or ISBNResearchpeer-review

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N1 - © 2014 AES. All rights reserved.

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N2 - Time correlation and decorrelation are well established tools to improve the signal to noise ratio of a system, yet they are often poorly understood. When several unwanted signals are correlated they are much easier to remove from uncorrelated wanted signals than vice versa, where a much poorer improvement is possible. A case in point is the removal of wind noise from microphone signals. The situation is further compounded when one or other of the signals is only partially correlated, or different spectral content is differently correlated. This paper looks at the theoretical improvement in signal to noise ratio when either the signal or the noise are correlated to different degrees. Application to real microphone signals and noise is discussed.

AB - Time correlation and decorrelation are well established tools to improve the signal to noise ratio of a system, yet they are often poorly understood. When several unwanted signals are correlated they are much easier to remove from uncorrelated wanted signals than vice versa, where a much poorer improvement is possible. A case in point is the removal of wind noise from microphone signals. The situation is further compounded when one or other of the signals is only partially correlated, or different spectral content is differently correlated. This paper looks at the theoretical improvement in signal to noise ratio when either the signal or the noise are correlated to different degrees. Application to real microphone signals and noise is discussed.

M3 - Conference contribution with ISSN or ISBN

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EP - 0

BT - Proceedings of the 137th AES Convention

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