{"id":"https://openalex.org/W2147352483","doi":"https://doi.org/10.1109/tsp.2013.2286113","title":"Noncircular Complex ICA by Generalized Householder Reflections","display_name":"Noncircular Complex ICA by Generalized Householder Reflections","publication_year":2013,"publication_date":"2013-10-17","ids":{"openalex":"https://openalex.org/W2147352483","doi":"https://doi.org/10.1109/tsp.2013.2286113","mag":"2147352483"},"language":"en","primary_location":{"id":"doi:10.1109/tsp.2013.2286113","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2013.2286113","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Signal Processing","raw_type":"journal-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/A5100639669","display_name":"Xi-Lin Li","orcid":null},"institutions":[{"id":"https://openalex.org/I4210154986","display_name":"HealthMedia (United States)","ror":"https://ror.org/05qevt293","country_code":"US","type":"company","lineage":["https://openalex.org/I4210154986"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xi-Lin Li","raw_affiliation_strings":["Fortemedia Inc., Sunnyvale, CA","Fortemedia Inc., Sunnyvale, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fortemedia Inc., Sunnyvale, CA","institution_ids":[]},{"raw_affiliation_string":"Fortemedia Inc., Sunnyvale, CA, USA","institution_ids":["https://openalex.org/I4210154986"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060798483","display_name":"T\u00fclay Adal\u0131","orcid":"https://orcid.org/0000-0003-0594-2796"},"institutions":[{"id":"https://openalex.org/I79272384","display_name":"University of Maryland, Baltimore County","ror":"https://ror.org/02qskvh78","country_code":"US","type":"education","lineage":["https://openalex.org/I79272384"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tulay Adali","raw_affiliation_strings":["Dept. of Comput. Sci. & Electr. Eng., Univ. of Maryland, Baltimore County, Baltimore, MD, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Comput. Sci. & Electr. Eng., Univ. of Maryland, Baltimore County, Baltimore, MD, USA","institution_ids":["https://openalex.org/I79272384"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.9523,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.76832638,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"61","issue":"24","first_page":"6423","last_page":"6430"},"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/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9832000136375427,"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/T10320","display_name":"Neural Networks and Applications","score":0.9732999801635742,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/independent-component-analysis","display_name":"Independent component analysis","score":0.859199583530426},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.6783356666564941},{"id":"https://openalex.org/keywords/blind-signal-separation","display_name":"Blind signal separation","score":0.6569811701774597},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5755935907363892},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5676103830337524},{"id":"https://openalex.org/keywords/row-and-column-spaces","display_name":"Row and column spaces","score":0.5644773840904236},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.523094892501831},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.47768741846084595},{"id":"https://openalex.org/keywords/separation","display_name":"Separation (statistics)","score":0.46817746758461},{"id":"https://openalex.org/keywords/source-separation","display_name":"Source separation","score":0.4474159777164459},{"id":"https://openalex.org/keywords/row","display_name":"Row","score":0.42141416668891907},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41673731803894043},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3977195620536804},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.36873841285705566},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3314201831817627},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.1256600320339203},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.1197364330291748},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.10409709811210632}],"concepts":[{"id":"https://openalex.org/C51432778","wikidata":"https://www.wikidata.org/wiki/Q1259145","display_name":"Independent component analysis","level":2,"score":0.859199583530426},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.6783356666564941},{"id":"https://openalex.org/C120317606","wikidata":"https://www.wikidata.org/wiki/Q17105967","display_name":"Blind signal separation","level":3,"score":0.6569811701774597},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5755935907363892},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5676103830337524},{"id":"https://openalex.org/C104140500","wikidata":"https://www.wikidata.org/wiki/Q2088159","display_name":"Row and column spaces","level":3,"score":0.5644773840904236},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.523094892501831},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.47768741846084595},{"id":"https://openalex.org/C2776061190","wikidata":"https://www.wikidata.org/wiki/Q7451805","display_name":"Separation (statistics)","level":2,"score":0.46817746758461},{"id":"https://openalex.org/C2776864781","wikidata":"https://www.wikidata.org/wiki/Q52617913","display_name":"Source separation","level":2,"score":0.4474159777164459},{"id":"https://openalex.org/C135598885","wikidata":"https://www.wikidata.org/wiki/Q1366302","display_name":"Row","level":2,"score":0.42141416668891907},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41673731803894043},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3977195620536804},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36873841285705566},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3314201831817627},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.1256600320339203},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.1197364330291748},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.10409709811210632},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"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/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tsp.2013.2286113","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2013.2286113","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Signal Processing","raw_type":"journal-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.642.2511","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.642.2511","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.csee.umbc.edu/~adali/pubs/IEEEpubs/TSP2013li.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.4000000059604645,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W1517767549","https://openalex.org/W1868590549","https://openalex.org/W1972087067","https://openalex.org/W1974388905","https://openalex.org/W1977067929","https://openalex.org/W1983821361","https://openalex.org/W1999766892","https://openalex.org/W2000397825","https://openalex.org/W2003335470","https://openalex.org/W2055637322","https://openalex.org/W2061811442","https://openalex.org/W2065234731","https://openalex.org/W2092590148","https://openalex.org/W2095632977","https://openalex.org/W2095950579","https://openalex.org/W2115074110","https://openalex.org/W2115874509","https://openalex.org/W2123649031","https://openalex.org/W2124757684","https://openalex.org/W2127737934","https://openalex.org/W2128967371","https://openalex.org/W2132796249","https://openalex.org/W2140638323","https://openalex.org/W2143646747","https://openalex.org/W2144935618","https://openalex.org/W2153999007","https://openalex.org/W2154488158","https://openalex.org/W2164452510","https://openalex.org/W2166288622","https://openalex.org/W2533867596","https://openalex.org/W3100792434","https://openalex.org/W4242259102","https://openalex.org/W4300246981","https://openalex.org/W6631150530"],"related_works":["https://openalex.org/W2390344110","https://openalex.org/W2364896863","https://openalex.org/W2361066326","https://openalex.org/W2107364365","https://openalex.org/W2046761971","https://openalex.org/W2118307209","https://openalex.org/W1785857632","https://openalex.org/W4281722104","https://openalex.org/W2187523794","https://openalex.org/W1503525627"],"abstract_inverted_index":{"We":[0,28],"develop":[1],"an":[2],"efficient":[3],"algorithm":[4,32],"for":[5],"noncircular":[6],"complex":[7,37],"independent":[8],"component":[9],"analysis":[10],"(ICA)":[11],"by":[12],"optimizing":[13],"the":[14,30,34,50,53,61,66,70],"rows":[15],"of":[16,36,52,69],"separation":[17,35],"matrix":[18],"independently":[19],"using":[20],"a":[21,45],"generalized":[22,38],"Householder":[23],"reflector":[24],"and":[25,43,64],"Newton":[26],"method.":[27],"apply":[29],"new":[31,71],"to":[33,48,59],"Gaussian":[39],"distributed":[40],"(GGD)":[41],"sources,":[42],"propose":[44],"convenient":[46],"way":[47],"learn":[49],"noncircularity":[51],"sources.":[54],"Simulation":[55],"results":[56],"are":[57],"reported":[58],"study":[60],"convergence":[62],"behavior,":[63],"confirm":[65],"superior":[67],"performance":[68],"algorithm.":[72]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":1},{"year":2014,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}