{"id":"https://openalex.org/W2106395400","doi":"https://doi.org/10.1109/icassp.2006.1661412","title":"Post-Nonlinear Undercomplete Blind Signal Separation: A Bayesian Approach","display_name":"Post-Nonlinear Undercomplete Blind Signal Separation: A Bayesian Approach","publication_year":2006,"publication_date":"2006-08-03","ids":{"openalex":"https://openalex.org/W2106395400","doi":"https://doi.org/10.1109/icassp.2006.1661412","mag":"2106395400"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2006.1661412","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2006.1661412","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2006 IEEE International Conference on Acoustics Speed and Signal Processing Proceedings","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"C. Wei","orcid":null},"institutions":[{"id":"https://openalex.org/I84884186","display_name":"Newcastle University","ror":"https://ror.org/01kj2bm70","country_code":"GB","type":"education","lineage":["https://openalex.org/I84884186"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"C. Wei","raw_affiliation_strings":["University of Newcastle, UK","Newcastle upon Tyne Univ"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Newcastle, UK","institution_ids":["https://openalex.org/I84884186"]},{"raw_affiliation_string":"Newcastle upon Tyne Univ","institution_ids":["https://openalex.org/I84884186"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110604406","display_name":"L.C. Khor","orcid":null},"institutions":[{"id":"https://openalex.org/I84884186","display_name":"Newcastle University","ror":"https://ror.org/01kj2bm70","country_code":"GB","type":"education","lineage":["https://openalex.org/I84884186"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"L.C. Khor","raw_affiliation_strings":["University of Newcastle, UK","Newcastle upon Tyne Univ"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Newcastle, UK","institution_ids":["https://openalex.org/I84884186"]},{"raw_affiliation_string":"Newcastle upon Tyne Univ","institution_ids":["https://openalex.org/I84884186"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084431277","display_name":"Wai Lok Woo","orcid":"https://orcid.org/0000-0002-8698-7605"},"institutions":[{"id":"https://openalex.org/I84884186","display_name":"Newcastle University","ror":"https://ror.org/01kj2bm70","country_code":"GB","type":"education","lineage":["https://openalex.org/I84884186"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"W.L. Woo","raw_affiliation_strings":["University of Newcastle, UK","Newcastle upon Tyne Univ"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Newcastle, UK","institution_ids":["https://openalex.org/I84884186"]},{"raw_affiliation_string":"Newcastle upon Tyne Univ","institution_ids":["https://openalex.org/I84884186"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5112012109","display_name":"S.S. Dlay","orcid":null},"institutions":[{"id":"https://openalex.org/I84884186","display_name":"Newcastle University","ror":"https://ror.org/01kj2bm70","country_code":"GB","type":"education","lineage":["https://openalex.org/I84884186"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"S.S. Dlay","raw_affiliation_strings":["University of Newcastle, UK","Newcastle upon Tyne Univ"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Newcastle, UK","institution_ids":["https://openalex.org/I84884186"]},{"raw_affiliation_string":"Newcastle upon Tyne Univ","institution_ids":["https://openalex.org/I84884186"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I84884186"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"5","issue":null,"first_page":"V","last_page":"861"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9926000237464905,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9746999740600586,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.836140513420105},{"id":"https://openalex.org/keywords/blind-signal-separation","display_name":"Blind signal separation","score":0.7197479009628296},{"id":"https://openalex.org/keywords/maximum-a-posteriori-estimation","display_name":"Maximum a posteriori estimation","score":0.7050775289535522},{"id":"https://openalex.org/keywords/mixing","display_name":"Mixing (physics)","score":0.6775652766227722},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5727376937866211},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.5599135756492615},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5423763990402222},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"Multilayer perceptron","score":0.4857335686683655},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.46880629658699036},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.4665534198284149},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.4265376031398773},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.41650086641311646},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.41558128595352173},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4125509560108185},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.38461506366729736},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.36740612983703613},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1645086109638214}],"concepts":[{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.836140513420105},{"id":"https://openalex.org/C120317606","wikidata":"https://www.wikidata.org/wiki/Q17105967","display_name":"Blind signal separation","level":3,"score":0.7197479009628296},{"id":"https://openalex.org/C9810830","wikidata":"https://www.wikidata.org/wiki/Q635384","display_name":"Maximum a posteriori estimation","level":3,"score":0.7050775289535522},{"id":"https://openalex.org/C138777275","wikidata":"https://www.wikidata.org/wiki/Q6884054","display_name":"Mixing (physics)","level":2,"score":0.6775652766227722},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5727376937866211},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.5599135756492615},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5423763990402222},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.4857335686683655},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.46880629658699036},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.4665534198284149},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4265376031398773},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.41650086641311646},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.41558128595352173},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4125509560108185},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38461506366729736},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.36740612983703613},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1645086109638214},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2006.1661412","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2006.1661412","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2006 IEEE International Conference on Acoustics Speed and Signal Processing Proceedings","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W2036816056","https://openalex.org/W2037427014","https://openalex.org/W2046410761","https://openalex.org/W2088551704","https://openalex.org/W2119647652","https://openalex.org/W2125030400","https://openalex.org/W2143163931","https://openalex.org/W2146871592","https://openalex.org/W2165124740"],"related_works":["https://openalex.org/W1663203009","https://openalex.org/W4309133645","https://openalex.org/W2076543106","https://openalex.org/W2523437662","https://openalex.org/W89844371","https://openalex.org/W2019891950","https://openalex.org/W2085842814","https://openalex.org/W4286643620","https://openalex.org/W4387048144","https://openalex.org/W2492135063"],"abstract_inverted_index":{"The":[0,16,53,94],"post-nonlinear":[1],"undercomplete":[2],"blind":[3],"signal":[4],"separation":[5],"problem":[6],"is":[7,56,97,103],"solved":[8],"by":[9,58],"a":[10,31,33,59,91,106],"Bayesian":[11],"approach":[12,139],"in":[13,83,105],"this":[14],"paper.":[15],"proposed":[17,67,124],"algorithm":[18,38],"applies":[19],"the":[20,26,41,47,50,69,75,78,100,120,123],"generalized":[21],"Gaussian":[22],"model":[23],"to":[24,39,90,118,137],"approximate":[25],"prior":[27],"distribution":[28],"probability":[29],"and":[30,46,74],"maximum":[32],"posteriori":[34],"(MAP)":[35],"based":[36,110],"learning":[37],"estimate":[40],"source":[42,70],"signals,":[43,71],"mixing":[44,51,54,72],"matrix":[45,73],"nonlinearity":[48,55],"of":[49,77,122,129],"process.":[52],"modeled":[57],"multilayer":[60],"perceptron":[61],"(MLP)":[62],"neural":[63],"network.":[64],"In":[65],"our":[66],"algorithm,":[68],"parameters":[76],"MLP":[79],"are":[80],"iteratively":[81],"updated":[82],"an":[84],"alternate":[85],"manner":[86],"until":[87],"they":[88],"converges":[89],"fixed":[92],"value.":[93],"noise":[95],"variance":[96],"regarded":[98],"as":[99],"hyperparameter":[101],"which":[102],"estimated":[104],"closed":[107],"form.":[108],"Simulations":[109],"on":[111],"real":[112],"audio":[113],"have":[114],"been":[115,133],"carried":[116],"out":[117],"investigate":[119],"efficacy":[121],"algorithm.":[125],"A":[126],"performance":[127],"gain":[128],"over":[130],"125%":[131],"has":[132],"achieved":[134],"when":[135],"compared":[136],"linear":[138]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
