Blind source separation based on time-frequency signal representations.

Blind source separation consists of recovering a set of signals of which only instantaneous linear mixtures are observed. Thus far, this problem has been solved using statistical information available on the source signals. This paper introduces a new blind source separation approach exploiting the difference in the time-frequency (t-f) signatures of the sources to be separated. The approach is based on the diagonalization of a combined set of "spatial t-f distributions." In contrast to existing techniques, the proposed approach allows the separation of Gaussian sources with identical spectral shape but with different t-f localization properties. The effects of spreading the noise power while localizing the source energy in the t-f domain amounts to increasing the robustness of the proposed approach with respect to noise and, hence, improved performance. Asymptotic performance analysis and numerical simulations are provided.

Main Author: Belouchrani, Adel.
Other Authors: Amin, Moeness G.
Language: English
Published: 1998
Online Access: http://ezproxy.villanova.edu/login?url=https://digital.library.villanova.edu/Item/vudl:173186
PID vudl:173186
id vudl:173186
modeltype_str_mv vudl-system:CoreModel
vudl-system:CollectionModel
vudl-system:ResourceCollection
datastream_str_mv DC
PARENT-QUERY
PARENT-LIST-RAW
PARENT-LIST
MEMBER-QUERY
MEMBER-LIST-RAW
LEGACY-METS
LICENSE
AGENTS
PROCESS-MD
THUMBNAIL
STRUCTMAP
RELS-EXT
hierarchytype
sequence_vudl_173023_str 0000000055
has_order_str no
hierarchy_top_id vudl:171664
hierarchy_top_title Villanova Digital Collection
hierarchy_parent_id vudl:173023
hierarchy_parent_title Amin Moeness
hierarchy_sequence 0000000055
hierarchy_first_parent_id_str vudl:173186
hierarchy_sequence_sort_str 0000000055
hierarchy_all_parents_str_mv vudl:172968
vudl:171664
vudl:173023
first_indexed 2014-01-11T21:57:09Z
last_indexed 2014-01-11T21:57:09Z
recordtype vudl
fullrecord <root> <url> http://digital.library.villanova.edu/files/vudl:173186/DC </url> <thumbnail> http://digital.library.villanova.edu/files/vudl:173186/THUMBNAIL </thumbnail> </root>
spelling
institution Villanova University
collection Digital Library
language English
dc_source_str_mv IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 46, NO. 11, NOVEMBER 1998.
author Belouchrani, Adel.
author_s Belouchrani, Adel.
spellingShingle Belouchrani, Adel.
Blind source separation based on time-frequency signal representations.
author-letter Belouchrani, Adel.
author_sort_str Belouchrani, Adel.
author2 Amin, Moeness G.
author2Str Amin, Moeness G.
dc_title_str Blind source separation based on time-frequency signal representations.
title Blind source separation based on time-frequency signal representations.
title_short Blind source separation based on time-frequency signal representations.
title_full Blind source separation based on time-frequency signal representations.
title_fullStr Blind source separation based on time-frequency signal representations.
title_full_unstemmed Blind source separation based on time-frequency signal representations.
collection_title_sort_str blind source separation based on time-frequency signal representations.
title_sort blind source separation based on time-frequency signal representations.
description Blind source separation consists of recovering a set of signals of which only instantaneous linear mixtures are observed. Thus far, this problem has been solved using statistical information available on the source signals. This paper introduces a new blind source separation approach exploiting the difference in the time-frequency (t-f) signatures of the sources to be separated. The approach is based on the diagonalization of a combined set of "spatial t-f distributions." In contrast to existing techniques, the proposed approach allows the separation of Gaussian sources with identical spectral shape but with different t-f localization properties. The effects of spreading the noise power while localizing the source energy in the t-f domain amounts to increasing the robustness of the proposed approach with respect to noise and, hence, improved performance. Asymptotic performance analysis and numerical simulations are provided.
publishDate 1998
normalized_sort_date 1998-01-01T00:00:00Z
dc_date_str 1998
license_str protected
REPOSITORYNAME FgsRepos
REPOSBASEURL http://hades.library.villanova.edu:8088/fedora
fgs.state Active
fgs.label Blind source separation based on time-frequency signal representations.
fgs.ownerId diglibEditor
fgs.createdDate 2013-01-22T02:37:21.001Z
fgs.lastModifiedDate 2013-12-05T17:02:23.864Z
dc.title Blind source separation based on time-frequency signal representations.
dc.creator Belouchrani, Adel.
Amin, Moeness G.
dc.description Blind source separation consists of recovering a set of signals of which only instantaneous linear mixtures are observed. Thus far, this problem has been solved using statistical information available on the source signals. This paper introduces a new blind source separation approach exploiting the difference in the time-frequency (t-f) signatures of the sources to be separated. The approach is based on the diagonalization of a combined set of "spatial t-f distributions." In contrast to existing techniques, the proposed approach allows the separation of Gaussian sources with identical spectral shape but with different t-f localization properties. The effects of spreading the noise power while localizing the source energy in the t-f domain amounts to increasing the robustness of the proposed approach with respect to noise and, hence, improved performance. Asymptotic performance analysis and numerical simulations are provided.
dc.date 1998
dc.identifier vudl:173186
dc.source IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 46, NO. 11, NOVEMBER 1998.
dc.language en
license.mdRef http://digital.library.villanova.edu/copyright.html
agent.name Falvey Memorial Library, Villanova University
KHL
has_thumbnail true
THUMBNAIL_contentDigest_type MD5
THUMBNAIL_contentDigest_digest 203c69e18f4f46c81e9892448d2c07cd
THUMBNAIL_contentLocation_type INTERNAL_ID
THUMBNAIL_contentLocation_ref http://hades.library.villanova.edu:8088/fedora/get/vudl:173186/THUMBNAIL/2013-01-22T02:37:22.832Z
relsext.hasModel info:fedora/vudl-system:CoreModel
info:fedora/vudl-system:CollectionModel
info:fedora/vudl-system:ResourceCollection
relsext.itemID oai:digital.library.villanova.edu:vudl:173186
relsext.isMemberOf info:fedora/vudl:173023
relsext.hasLegacyURL http://digital.library.villanova.edu/Villanova%20Digital%20Collection/Faculty%20Fulltext/Amin%20Moeness/AminMoeness-b0363eea-086c-4b62-9e0f-8ed578ee050c.xml
relsext.sortOn title
relsext.sequence vudl:173023#55
_version_ 1504162994890735616
score 13.471796
subpages