{"id":"https://openalex.org/W3031924404","doi":"https://doi.org/10.1109/tsp.2020.2997803","title":"Unified and Self-Stabilized Parallel Algorithm for Multiple Generalized Eigenpairs Extraction","display_name":"Unified and Self-Stabilized Parallel Algorithm for Multiple Generalized Eigenpairs Extraction","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3031924404","doi":"https://doi.org/10.1109/tsp.2020.2997803","mag":"3031924404"},"language":"en","primary_location":{"id":"doi:10.1109/tsp.2020.2997803","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2020.2997803","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/A5033624629","display_name":"Xiangyu Kong","orcid":"https://orcid.org/0000-0003-2084-7826"},"institutions":[{"id":"https://openalex.org/I4210130660","display_name":"Xi'an High Tech University","ror":"https://ror.org/03vt7za95","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210130660"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangyu Kong","raw_affiliation_strings":["Xi'an Research Institute of High Technology, Xi'an, China"],"raw_orcid":"https://orcid.org/0000-0003-2084-7826","affiliations":[{"raw_affiliation_string":"Xi'an Research Institute of High Technology, Xi'an, China","institution_ids":["https://openalex.org/I4210130660"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053004844","display_name":"Boyang Du","orcid":"https://orcid.org/0000-0002-7101-9425"},"institutions":[{"id":"https://openalex.org/I4210130660","display_name":"Xi'an High Tech University","ror":"https://ror.org/03vt7za95","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210130660"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Boyang Du","raw_affiliation_strings":["Xi'an Research Institute of High Technology, Xi'an, China"],"raw_orcid":"https://orcid.org/0000-0002-7101-9425","affiliations":[{"raw_affiliation_string":"Xi'an Research Institute of High Technology, Xi'an, China","institution_ids":["https://openalex.org/I4210130660"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013494616","display_name":"Xiaowei Feng","orcid":"https://orcid.org/0000-0002-5123-2069"},"institutions":[{"id":"https://openalex.org/I4210130660","display_name":"Xi'an High Tech University","ror":"https://ror.org/03vt7za95","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210130660"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaowei Feng","raw_affiliation_strings":["Xi'an Research Institute of High Technology, Xi'an, China"],"raw_orcid":"https://orcid.org/0000-0002-5123-2069","affiliations":[{"raw_affiliation_string":"Xi'an Research Institute of High Technology, Xi'an, China","institution_ids":["https://openalex.org/I4210130660"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5011262638","display_name":"Jiayu Luo","orcid":"https://orcid.org/0000-0003-3453-2286"},"institutions":[{"id":"https://openalex.org/I4210130660","display_name":"Xi'an High Tech University","ror":"https://ror.org/03vt7za95","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210130660"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiayu Luo","raw_affiliation_strings":["Xi'an Research Institute of High Technology, Xi'an, China"],"raw_orcid":"https://orcid.org/0000-0003-3453-2286","affiliations":[{"raw_affiliation_string":"Xi'an Research Institute of High Technology, Xi'an, China","institution_ids":["https://openalex.org/I4210130660"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210130660"],"apc_list":null,"apc_paid":null,"fwci":0.297,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.51953125,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":"68","issue":null,"first_page":"3644","last_page":"3659"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9984999895095825,"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":0.9984999895095825,"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/T11236","display_name":"Control Systems and Identification","score":0.9980999827384949,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9976999759674072,"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/algorithm","display_name":"Algorithm","score":0.665325403213501},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.580250084400177},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.5409923195838928},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.47635936737060547},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.4761505126953125},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.43190592527389526},{"id":"https://openalex.org/keywords/minor","display_name":"Minor (academic)","score":0.4166768193244934},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4119868874549866},{"id":"https://openalex.org/keywords/generalized-eigenvector","display_name":"Generalized eigenvector","score":0.4103180170059204},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.33521485328674316},{"id":"https://openalex.org/keywords/symmetric-matrix","display_name":"Symmetric matrix","score":0.23921948671340942},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.21293863654136658},{"id":"https://openalex.org/keywords/state-transition-matrix","display_name":"State-transition matrix","score":0.08270895481109619}],"concepts":[{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.665325403213501},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.580250084400177},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.5409923195838928},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.47635936737060547},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.4761505126953125},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.43190592527389526},{"id":"https://openalex.org/C2779760435","wikidata":"https://www.wikidata.org/wiki/Q5396169","display_name":"Minor (academic)","level":2,"score":0.4166768193244934},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4119868874549866},{"id":"https://openalex.org/C147925508","wikidata":"https://www.wikidata.org/wiki/Q970767","display_name":"Generalized eigenvector","level":5,"score":0.4103180170059204},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.33521485328674316},{"id":"https://openalex.org/C54848796","wikidata":"https://www.wikidata.org/wiki/Q339011","display_name":"Symmetric matrix","level":3,"score":0.23921948671340942},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.21293863654136658},{"id":"https://openalex.org/C22629506","wikidata":"https://www.wikidata.org/wiki/Q7602993","display_name":"State-transition matrix","level":4,"score":0.08270895481109619},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tsp.2020.2997803","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2020.2997803","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"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2862529042","display_name":null,"funder_award_id":"2020JM-356","funder_id":"https://openalex.org/F4320324173","funder_display_name":"Natural Science Foundation of Shaanxi Province"},{"id":"https://openalex.org/G417141083","display_name":null,"funder_award_id":"61903375","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5504500574","display_name":null,"funder_award_id":"61673387","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7535277257","display_name":null,"funder_award_id":"61833016","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320324173","display_name":"Natural Science Foundation of Shaanxi Province","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W5731987","https://openalex.org/W188867245","https://openalex.org/W641369966","https://openalex.org/W1489133580","https://openalex.org/W1548802052","https://openalex.org/W1976045444","https://openalex.org/W1984938247","https://openalex.org/W1990701162","https://openalex.org/W2024834894","https://openalex.org/W2040386146","https://openalex.org/W2045362262","https://openalex.org/W2048055233","https://openalex.org/W2053055988","https://openalex.org/W2059586807","https://openalex.org/W2073843710","https://openalex.org/W2074241406","https://openalex.org/W2091353418","https://openalex.org/W2095657361","https://openalex.org/W2097515270","https://openalex.org/W2098654213","https://openalex.org/W2099476272","https://openalex.org/W2104309817","https://openalex.org/W2104684272","https://openalex.org/W2108196196","https://openalex.org/W2116019577","https://openalex.org/W2119538061","https://openalex.org/W2121515090","https://openalex.org/W2123957576","https://openalex.org/W2130642135","https://openalex.org/W2133515443","https://openalex.org/W2135591374","https://openalex.org/W2140984045","https://openalex.org/W2144689866","https://openalex.org/W2145211141","https://openalex.org/W2146392814","https://openalex.org/W2166604943","https://openalex.org/W2334834948","https://openalex.org/W2531843432","https://openalex.org/W2552410236","https://openalex.org/W2568342123","https://openalex.org/W2797003661","https://openalex.org/W4205778870","https://openalex.org/W4312258136","https://openalex.org/W6676123182"],"related_works":["https://openalex.org/W2000169474","https://openalex.org/W1972373683","https://openalex.org/W1585144779","https://openalex.org/W4247119539","https://openalex.org/W2087767175","https://openalex.org/W1982051704","https://openalex.org/W189179360","https://openalex.org/W2045525193","https://openalex.org/W2150550868","https://openalex.org/W2051754724"],"abstract_inverted_index":{"Generalized":[0,31],"eigenvalue":[1],"decomposition":[2],"has":[3,197],"many":[4],"advantages":[5],"when":[6],"it":[7],"is":[8,101,109],"applied":[9],"in":[10,43,73,92],"modern":[11],"signal":[12],"processing.":[13],"Compared":[14],"with":[15],"other":[16],"methods,":[17],"neural":[18,37],"network":[19,38],"model-based":[20],"algorithms":[21,34,52,169],"provide":[22],"an":[23],"efficient":[24],"way":[25,95],"to":[26,215],"solve":[27],"such":[28],"problems":[29],"online.":[30],"feature":[32],"extraction":[33,88,159],"based":[35,103],"on":[36,104,137],"models":[39],"have":[40],"been":[41],"described":[42],"the":[44,47,50,56,87,99,120,132,141,167,179,185,218,221],"literature.":[45],"However,":[46],"majority":[48],"of":[49,89,166,178,220],"existing":[51,168],"can":[53,127,144,170],"only":[54],"extract":[55,63],"principal":[57,64,113,122],"generalized":[58,67,112,125,147,161],"eigenvector(s)":[59],"or":[60],"eigensubspace.":[61],"To":[62],"and":[65,82,114,123,160,175,188,204,211],"minor":[66,115,124],"eigenvectors":[68],"from":[69],"two":[70,76],"vector":[71],"sequences,":[72],"this":[74],"paper,":[75],"different":[77],"information":[78,106],"criteria":[79],"are":[80,182,213],"proposed,":[81],"a":[83,93,198],"unified":[84],"algorithm":[85,143,152,181,196],"for":[86,111],"multiple":[90,146],"components":[91],"parallel":[94,158],"by":[96],"simply":[97],"altering":[98],"sign":[100],"derived":[102],"these":[105,138],"criteria,":[107],"which":[108],"feasible":[110],"component":[116],"analysis.":[117],"Moreover,":[118],"all":[119],"corresponding":[121],"eigenvalues":[126],"be":[128],"extracted":[129],"simultaneously":[130],"because":[131],"desired":[133],"equilibrium":[134],"point":[135],"depends":[136],"values.":[139],"Thus,":[140],"proposed":[142,151,180,195,222],"perform":[145],"eigenpair":[148,162],"extraction.":[149],"The":[150,172,194],"possesses":[153],"four":[154],"properties:":[155],"unification,":[156],"self-stability,":[157],"extraction,":[163],"that":[164],"few":[165],"encompass.":[171],"global":[173],"convergence":[174,200],"self-stability":[176],"property":[177],"proved":[183],"through":[184],"Lyapunov":[186],"method":[187],"ordinary":[189],"differential":[190],"equation":[191],"method,":[192],"respectively.":[193],"fast":[199],"speed,":[201],"high":[202],"precision":[203],"strong":[205],"tracking":[206],"ability.":[207],"Finally,":[208],"numerical":[209],"examples":[210],"applications":[212],"explored":[214],"further":[216],"demonstrate":[217],"efficiency":[219],"algorithm.":[223]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}