Time domain reconstruction of spatial sound fields using compressed sensing

Time domain reconstruction of spatial sound fields using compressed sensing

A novel technique for time domain spatial sound reproduction using compressed sensing is presented. The presented technique is based on the application of compressed sensing theory, which is used to improve the accuracy of the reconstructed sound field. In addition, singular value decomposition is a...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Wabnitz, Andrew, Epain, Nicolas, van Schaik, Andre, Jin, Craig
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Acoustic signal processing
Arrays
Compressed sensing
Harmonic analysis
Image reconstruction
Loudspeakers
Optimization
Receivers
Signal reconstruction
Sparse matrices
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 468
container_issue
container_start_page 465
container_title
container_volume
creator Wabnitz, Andrew
Epain, Nicolas
van Schaik, Andre
Jin, Craig
description A novel technique for time domain spatial sound reproduction using compressed sensing is presented. The presented technique is based on the application of compressed sensing theory, which is used to improve the accuracy of the reconstructed sound field. In addition, singular value decomposition is also applied, which acts to significantly reduce the size of the data set to process, thus making it efficient and realisable for real-time applications. Results are presented from the preliminary performance evaluation of the compressed sensing technique in comparison to the Higher Order Ambisonic reconstruction technique.
doi_str_mv 10.1109/ICASSP.2011.5946441
format Conference Proceeding
fullrecord <record><control><sourceid>ieee_6IE</sourceid><recordid>TN_cdi_ieee_primary_5946441</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>5946441</ieee_id><sourcerecordid>5946441</sourcerecordid><originalsourceid>FETCH-LOGICAL-i175t-f2cb0a39dcecf988a5c6ce6f5387aab4a43f8435358da6dff0341242045073fa3</originalsourceid><addsrcrecordid>eNo1UMtKw0AAXF9grPmCXvYHUvf9OErRKhYUWsFb2e5DVpLdkE0O_r0R61wGZmCYGQCWGK0wRvrueX2_272tCMJ4xTUTjOEzcIMZlxJxquU5qAiVusEafVyAWkv17yl0CSrMCWoEZvoa1KV8oRmCSMl1BV72sfPQ5c7EBAdvcyrjMNkx5gRzgKU3YzQtLHlKDoboW1fgVGL6hDZ3_eBL8Q4Wn36lW3AVTFt8feIFeH982K-fmu3rZl6wbSKWfGwCsUdkqHbW26CVMtwK60WYy0pjjswwGhSjnHLljHAhIMowYQQxjiQNhi7A8i83eu8P_RA7M3wfTr_QH6DSVBI</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>Time domain reconstruction of spatial sound fields using compressed sensing</title><source>IEEE Electronic Library (IEL) Conference Proceedings</source><creator>Wabnitz, Andrew ; Epain, Nicolas ; van Schaik, Andre ; Jin, Craig</creator><creatorcontrib>Wabnitz, Andrew ; Epain, Nicolas ; van Schaik, Andre ; Jin, Craig</creatorcontrib><description>A novel technique for time domain spatial sound reproduction using compressed sensing is presented. The presented technique is based on the application of compressed sensing theory, which is used to improve the accuracy of the reconstructed sound field. In addition, singular value decomposition is also applied, which acts to significantly reduce the size of the data set to process, thus making it efficient and realisable for real-time applications. Results are presented from the preliminary performance evaluation of the compressed sensing technique in comparison to the Higher Order Ambisonic reconstruction technique.</description><identifier>ISSN: 1520-6149</identifier><identifier>ISBN: 9781457705380</identifier><identifier>ISBN: 1457705389</identifier><identifier>EISSN: 2379-190X</identifier><identifier>EISBN: 1457705397</identifier><identifier>EISBN: 9781457705373</identifier><identifier>EISBN: 9781457705397</identifier><identifier>EISBN: 1457705370</identifier><identifier>DOI: 10.1109/ICASSP.2011.5946441</identifier><language>eng</language><publisher>IEEE</publisher><subject>Acoustic signal processing ; Arrays ; Compressed sensing ; Harmonic analysis ; Image reconstruction ; Loudspeakers ; Optimization ; Receivers ; Signal reconstruction ; Sparse matrices</subject><ispartof>2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2011, p.465-468</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/5946441$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,2056,27924,54919</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/5946441$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Wabnitz, Andrew</creatorcontrib><creatorcontrib>Epain, Nicolas</creatorcontrib><creatorcontrib>van Schaik, Andre</creatorcontrib><creatorcontrib>Jin, Craig</creatorcontrib><title>Time domain reconstruction of spatial sound fields using compressed sensing</title><title>2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)</title><addtitle>ICASSP</addtitle><description>A novel technique for time domain spatial sound reproduction using compressed sensing is presented. The presented technique is based on the application of compressed sensing theory, which is used to improve the accuracy of the reconstructed sound field. In addition, singular value decomposition is also applied, which acts to significantly reduce the size of the data set to process, thus making it efficient and realisable for real-time applications. Results are presented from the preliminary performance evaluation of the compressed sensing technique in comparison to the Higher Order Ambisonic reconstruction technique.</description><subject>Acoustic signal processing</subject><subject>Arrays</subject><subject>Compressed sensing</subject><subject>Harmonic analysis</subject><subject>Image reconstruction</subject><subject>Loudspeakers</subject><subject>Optimization</subject><subject>Receivers</subject><subject>Signal reconstruction</subject><subject>Sparse matrices</subject><issn>1520-6149</issn><issn>2379-190X</issn><isbn>9781457705380</isbn><isbn>1457705389</isbn><isbn>1457705397</isbn><isbn>9781457705373</isbn><isbn>9781457705397</isbn><isbn>1457705370</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2011</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNo1UMtKw0AAXF9grPmCXvYHUvf9OErRKhYUWsFb2e5DVpLdkE0O_r0R61wGZmCYGQCWGK0wRvrueX2_272tCMJ4xTUTjOEzcIMZlxJxquU5qAiVusEafVyAWkv17yl0CSrMCWoEZvoa1KV8oRmCSMl1BV72sfPQ5c7EBAdvcyrjMNkx5gRzgKU3YzQtLHlKDoboW1fgVGL6hDZ3_eBL8Q4Wn36lW3AVTFt8feIFeH982K-fmu3rZl6wbSKWfGwCsUdkqHbW26CVMtwK60WYy0pjjswwGhSjnHLljHAhIMowYQQxjiQNhi7A8i83eu8P_RA7M3wfTr_QH6DSVBI</recordid><startdate>201105</startdate><enddate>201105</enddate><creator>Wabnitz, Andrew</creator><creator>Epain, Nicolas</creator><creator>van Schaik, Andre</creator><creator>Jin, Craig</creator><general>IEEE</general><scope>6IE</scope><scope>6IH</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIO</scope></search><sort><creationdate>201105</creationdate><title>Time domain reconstruction of spatial sound fields using compressed sensing</title><author>Wabnitz, Andrew ; Epain, Nicolas ; van Schaik, Andre ; Jin, Craig</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-f2cb0a39dcecf988a5c6ce6f5387aab4a43f8435358da6dff0341242045073fa3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Acoustic signal processing</topic><topic>Arrays</topic><topic>Compressed sensing</topic><topic>Harmonic analysis</topic><topic>Image reconstruction</topic><topic>Loudspeakers</topic><topic>Optimization</topic><topic>Receivers</topic><topic>Signal reconstruction</topic><topic>Sparse matrices</topic><toplevel>online_resources</toplevel><creatorcontrib>Wabnitz, Andrew</creatorcontrib><creatorcontrib>Epain, Nicolas</creatorcontrib><creatorcontrib>van Schaik, Andre</creatorcontrib><creatorcontrib>Jin, Craig</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan (POP) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Xplore</collection><collection>IEEE Proceedings Order Plans (POP) 1998-present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Wabnitz, Andrew</au><au>Epain, Nicolas</au><au>van Schaik, Andre</au><au>Jin, Craig</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Time domain reconstruction of spatial sound fields using compressed sensing</atitle><btitle>2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)</btitle><stitle>ICASSP</stitle><date>2011-05</date><risdate>2011</risdate><spage>465</spage><epage>468</epage><pages>465-468</pages><issn>1520-6149</issn><eissn>2379-190X</eissn><isbn>9781457705380</isbn><isbn>1457705389</isbn><eisbn>1457705397</eisbn><eisbn>9781457705373</eisbn><eisbn>9781457705397</eisbn><eisbn>1457705370</eisbn><abstract>A novel technique for time domain spatial sound reproduction using compressed sensing is presented. The presented technique is based on the application of compressed sensing theory, which is used to improve the accuracy of the reconstructed sound field. In addition, singular value decomposition is also applied, which acts to significantly reduce the size of the data set to process, thus making it efficient and realisable for real-time applications. Results are presented from the preliminary performance evaluation of the compressed sensing technique in comparison to the Higher Order Ambisonic reconstruction technique.</abstract><pub>IEEE</pub><doi>10.1109/ICASSP.2011.5946441</doi><tpages>4</tpages></addata></record>
fulltext fulltext_linktorsrc
identifier ISSN: 1520-6149
ispartof 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2011, p.465-468
issn 1520-6149
2379-190X
language eng
recordid cdi_ieee_primary_5946441
source IEEE Electronic Library (IEL) Conference Proceedings
subjects Acoustic signal processing
Arrays
Compressed sensing
Harmonic analysis
Image reconstruction
Loudspeakers
Optimization
Receivers
Signal reconstruction
Sparse matrices
title Time domain reconstruction of spatial sound fields using compressed sensing
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-10T19%3A21%3A13IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-ieee_6IE&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=Time%20domain%20reconstruction%20of%20spatial%20sound%20fields%20using%20compressed%20sensing&rft.btitle=2011%20IEEE%20International%20Conference%20on%20Acoustics,%20Speech%20and%20Signal%20Processing%20(ICASSP)&rft.au=Wabnitz,%20Andrew&rft.date=2011-05&rft.spage=465&rft.epage=468&rft.pages=465-468&rft.issn=1520-6149&rft.eissn=2379-190X&rft.isbn=9781457705380&rft.isbn_list=1457705389&rft_id=info:doi/10.1109/ICASSP.2011.5946441&rft_dat=%3Cieee_6IE%3E5946441%3C/ieee_6IE%3E%3Curl%3E%3C/url%3E&rft.eisbn=1457705397&rft.eisbn_list=9781457705373&rft.eisbn_list=9781457705397&rft.eisbn_list=1457705370&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=5946441&rfr_iscdi=true