{"id":"https://openalex.org/W2151985296","doi":"https://doi.org/10.1109/iscas.2003.1204948","title":"New hyperbolic source density models for blind source recovery score functions","display_name":"New hyperbolic source density models for blind source recovery score functions","publication_year":2003,"publication_date":"2003-11-20","ids":{"openalex":"https://openalex.org/W2151985296","doi":"https://doi.org/10.1109/iscas.2003.1204948","mag":"2151985296"},"language":"en","primary_location":{"id":"doi:10.1109/iscas.2003.1204948","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscas.2003.1204948","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2003 International Symposium on Circuits and Systems, 2003. ISCAS '03.","raw_type":"proceedings-article"},"type":"article","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":"https://openalex.org/A5108364605","display_name":"Khurram Waheed","orcid":null},"institutions":[{"id":"https://openalex.org/I87216513","display_name":"Michigan State University","ror":"https://ror.org/05hs6h993","country_code":"US","type":"education","lineage":["https://openalex.org/I87216513"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"K. Waheed","raw_affiliation_strings":["Circuits, Systems and Artificial Neural Networks Laboratory, Michigan State University, East Lansing, MI, USA"],"affiliations":[{"raw_affiliation_string":"Circuits, Systems and Artificial Neural Networks Laboratory, Michigan State University, East Lansing, MI, USA","institution_ids":["https://openalex.org/I87216513"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5048892243","display_name":"F.M. Salem","orcid":"https://orcid.org/0000-0001-9099-5635"},"institutions":[{"id":"https://openalex.org/I87216513","display_name":"Michigan State University","ror":"https://ror.org/05hs6h993","country_code":"US","type":"education","lineage":["https://openalex.org/I87216513"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"F.M. Salem","raw_affiliation_strings":["Circuits, Systems and Artificial Neural Networks Laboratory, Michigan State University, East Lansing, MI, USA"],"affiliations":[{"raw_affiliation_string":"Circuits, Systems and Artificial Neural Networks Laboratory, Michigan State University, East Lansing, MI, USA","institution_ids":["https://openalex.org/I87216513"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5108364605"],"corresponding_institution_ids":["https://openalex.org/I87216513"],"apc_list":null,"apc_paid":null,"fwci":2.3425,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.90063364,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":null,"biblio":{"volume":"3","issue":null,"first_page":"III","last_page":"32"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9997000098228455,"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":0.9997000098228455,"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":0.9836999773979187,"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"}},{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9634000062942505,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.6871936917304993},{"id":"https://openalex.org/keywords/probability-density-function","display_name":"Probability density function","score":0.6829025745391846},{"id":"https://openalex.org/keywords/cauchy-distribution","display_name":"Cauchy distribution","score":0.59292072057724},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5335436463356018},{"id":"https://openalex.org/keywords/kurtosis","display_name":"Kurtosis","score":0.515988826751709},{"id":"https://openalex.org/keywords/generalized-inverse-gaussian-distribution","display_name":"Generalized inverse Gaussian distribution","score":0.5133096575737},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.5121498107910156},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.45333442091941833},{"id":"https://openalex.org/keywords/generalized-normal-distribution","display_name":"Generalized normal distribution","score":0.44673842191696167},{"id":"https://openalex.org/keywords/density-estimation","display_name":"Density estimation","score":0.42936956882476807},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.42733603715896606},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.42410755157470703},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3498081564903259},{"id":"https://openalex.org/keywords/gaussian-random-field","display_name":"Gaussian random field","score":0.2796064019203186},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.22283720970153809},{"id":"https://openalex.org/keywords/normal-distribution","display_name":"Normal distribution","score":0.1652519702911377}],"concepts":[{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.6871936917304993},{"id":"https://openalex.org/C197055811","wikidata":"https://www.wikidata.org/wiki/Q207522","display_name":"Probability density function","level":2,"score":0.6829025745391846},{"id":"https://openalex.org/C49344536","wikidata":"https://www.wikidata.org/wiki/Q726441","display_name":"Cauchy distribution","level":2,"score":0.59292072057724},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5335436463356018},{"id":"https://openalex.org/C166963901","wikidata":"https://www.wikidata.org/wiki/Q287251","display_name":"Kurtosis","level":2,"score":0.515988826751709},{"id":"https://openalex.org/C18912344","wikidata":"https://www.wikidata.org/wiki/Q866810","display_name":"Generalized inverse Gaussian distribution","level":5,"score":0.5133096575737},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.5121498107910156},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.45333442091941833},{"id":"https://openalex.org/C171383496","wikidata":"https://www.wikidata.org/wiki/Q2497477","display_name":"Generalized normal distribution","level":3,"score":0.44673842191696167},{"id":"https://openalex.org/C189508267","wikidata":"https://www.wikidata.org/wiki/Q17088227","display_name":"Density estimation","level":3,"score":0.42936956882476807},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.42733603715896606},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.42410755157470703},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3498081564903259},{"id":"https://openalex.org/C51267290","wikidata":"https://www.wikidata.org/wiki/Q5527848","display_name":"Gaussian random field","level":4,"score":0.2796064019203186},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.22283720970153809},{"id":"https://openalex.org/C102094743","wikidata":"https://www.wikidata.org/wiki/Q133871","display_name":"Normal distribution","level":2,"score":0.1652519702911377},{"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/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iscas.2003.1204948","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscas.2003.1204948","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2003 International Symposium on Circuits and Systems, 2003. ISCAS '03.","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.7799999713897705,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W148455047","https://openalex.org/W184227589","https://openalex.org/W1512545811","https://openalex.org/W1514077900","https://openalex.org/W1517849739","https://openalex.org/W1558034244","https://openalex.org/W2022852240","https://openalex.org/W2121614598","https://openalex.org/W2146871592","https://openalex.org/W2611591252","https://openalex.org/W6607526506","https://openalex.org/W6750223540"],"related_works":["https://openalex.org/W2005453735","https://openalex.org/W2109705503","https://openalex.org/W2900306913","https://openalex.org/W2155489196","https://openalex.org/W2899196385","https://openalex.org/W2022240938","https://openalex.org/W2136743898","https://openalex.org/W1583602024","https://openalex.org/W2008489469","https://openalex.org/W2003279758"],"abstract_inverted_index":{"We":[0],"present":[1],"two":[2,95],"new":[3],"hyperbolic":[4,38],"source":[5,114],"probability":[6,39],"models":[7,26,97],"to":[8,68,119,159],"effectively":[9],"represent":[10,56],"sub-Gaussian":[11,43,61],"and":[12,19],"super-Gaussian":[13],"families":[14],"of":[15,48,60,81,91,110,133,142,155],"sources":[16],"for":[17,31,41,104,124],"dynamic":[18],"convolutive":[20,172],"Blind":[21,105,173],"Source":[22,106,174],"Recovery":[23,107,175],"(BSR).":[24],"Both":[25],"share":[27],"a":[28,57],"common":[29],"boundary":[30],"the":[32,42,49,69,74,82,121,125,130,143,152,156],"Gaussian":[33],"density":[34,51,85],"function.":[35],"The":[36,53,139,163],"proposed":[37,75,96,126,144,164],"model":[40,54,77],"densities":[44,62,65],"is":[45,78,136,148],"an":[46,79,88,100],"extension":[47,80],"Pearson":[50,71],"model.":[52],"can":[55],"broader":[58],"range":[59],"including":[63],"multi-modal":[64],"as":[66],"compared":[67],"original":[70],"Model.":[72],"Similarly,":[73],"super-gaussian":[76],"generalized":[83],"hyperbolic-Cauchy":[84],"function":[86,103],"with":[87],"added":[89],"degree":[90],"freedom.":[92],"Combining":[93],"these":[94],"we":[98],"propose":[99],"adaptive":[101,117,153],"score":[102,127],"from":[108],"mixtures":[109],"multiple":[111],"(and":[112],"unknown)":[113],"densities.":[115],"An":[116],"algorithm,":[118],"determine":[120],"regulation":[122],"parameters":[123],"function,":[128],"using":[129],"batch":[131],"kurtosis":[132],"BSR":[134],"output":[135],"also":[137],"presented.":[138],"primary":[140],"advantage":[141],"online":[145],"parameter":[146],"estimation":[147,154],"that":[149],"it":[150],"renders":[151],"demixing":[157],"network":[158],"be":[160],"completely":[161],"blind.":[162],"algorithms":[165],"have":[166],"been":[167],"extensively":[168],"used":[169],"in":[170],"multi-distribution":[171],"problems.":[176]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}