{"id":"https://openalex.org/W4288783425","doi":"https://doi.org/10.1109/lcomm.2022.3194961","title":"Source Number Estimation via Machine Learning Based on Eigenvalue Preprocessing","display_name":"Source Number Estimation via Machine Learning Based on Eigenvalue Preprocessing","publication_year":2022,"publication_date":"2022-07-29","ids":{"openalex":"https://openalex.org/W4288783425","doi":"https://doi.org/10.1109/lcomm.2022.3194961"},"language":"en","primary_location":{"id":"doi:10.1109/lcomm.2022.3194961","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lcomm.2022.3194961","pdf_url":null,"source":{"id":"https://openalex.org/S147316732","display_name":"IEEE Communications Letters","issn_l":"1089-7798","issn":["1089-7798","1558-2558","2373-7891"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310316002","host_organization_name":"IEEE Communications Society","host_organization_lineage":["https://openalex.org/P4310316002","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Communications Society","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 Communications Letters","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/A5070425562","display_name":"Shuai Zhou","orcid":"https://orcid.org/0000-0001-7574-9022"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuai Zhou","raw_affiliation_strings":["School of Telecommunications Engineering, Xidian University, Xi’an, China"],"raw_orcid":"https://orcid.org/0000-0001-7574-9022","affiliations":[{"raw_affiliation_string":"School of Telecommunications Engineering, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100440801","display_name":"Tao Li","orcid":"https://orcid.org/0000-0001-9968-2993"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Li","raw_affiliation_strings":["School of Telecommunications Engineering, Xidian University, Xi’an, China"],"raw_orcid":"https://orcid.org/0000-0001-9968-2993","affiliations":[{"raw_affiliation_string":"School of Telecommunications Engineering, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017026695","display_name":"Yongzhao Li","orcid":"https://orcid.org/0000-0003-2142-6652"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongzhao Li","raw_affiliation_strings":["School of Telecommunications Engineering, Xidian University, Xi’an, China"],"raw_orcid":"https://orcid.org/0000-0003-2142-6652","affiliations":[{"raw_affiliation_string":"School of Telecommunications Engineering, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100421972","display_name":"Rui Zhang","orcid":"https://orcid.org/0000-0001-9130-5739"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rui Zhang","raw_affiliation_strings":["School of Telecommunications Engineering, Xidian University, Xi’an, China"],"raw_orcid":"https://orcid.org/0000-0001-9130-5739","affiliations":[{"raw_affiliation_string":"School of Telecommunications Engineering, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029601945","display_name":"Yuhan Ruan","orcid":"https://orcid.org/0000-0003-4278-5662"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuhan Ruan","raw_affiliation_strings":["School of Telecommunications Engineering, Xidian University, Xi’an, China"],"raw_orcid":"https://orcid.org/0000-0003-4278-5662","affiliations":[{"raw_affiliation_string":"School of Telecommunications Engineering, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I149594827"],"apc_list":null,"apc_paid":null,"fwci":2.2624,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":{"value":0.88215607,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"26","issue":"10","first_page":"2360","last_page":"2364"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9994999766349792,"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/T10860","display_name":"Speech and Audio Processing","score":0.9994999766349792,"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/T10931","display_name":"Direction-of-Arrival Estimation Techniques","score":0.9991999864578247,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.996399998664856,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.8219177722930908},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7450994253158569},{"id":"https://openalex.org/keywords/covariance-matrix","display_name":"Covariance matrix","score":0.6583966612815857},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5911003351211548},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.5567827224731445},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.527525007724762},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.5139257907867432},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5017733573913574},{"id":"https://openalex.org/keywords/data-pre-processing","display_name":"Data pre-processing","score":0.4944784641265869},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4567921459674835},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.4487796425819397},{"id":"https://openalex.org/keywords/signal-to-noise-ratio","display_name":"Signal-to-noise ratio (imaging)","score":0.4446921646595001},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.44180166721343994},{"id":"https://openalex.org/keywords/estimation-theory","display_name":"Estimation theory","score":0.4199448227882385},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4103561043739319},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4087609350681305},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.18038102984428406},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16858771443367004},{"id":"https://openalex.org/keywords/digital-signal-processing","display_name":"Digital signal processing","score":0.14506438374519348}],"concepts":[{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.8219177722930908},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7450994253158569},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.6583966612815857},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5911003351211548},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.5567827224731445},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.527525007724762},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.5139257907867432},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5017733573913574},{"id":"https://openalex.org/C10551718","wikidata":"https://www.wikidata.org/wiki/Q5227332","display_name":"Data pre-processing","level":2,"score":0.4944784641265869},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4567921459674835},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.4487796425819397},{"id":"https://openalex.org/C13944312","wikidata":"https://www.wikidata.org/wiki/Q7512748","display_name":"Signal-to-noise ratio (imaging)","level":2,"score":0.4446921646595001},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.44180166721343994},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.4199448227882385},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4103561043739319},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4087609350681305},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.18038102984428406},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16858771443367004},{"id":"https://openalex.org/C84462506","wikidata":"https://www.wikidata.org/wiki/Q173142","display_name":"Digital signal processing","level":2,"score":0.14506438374519348},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"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/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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lcomm.2022.3194961","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lcomm.2022.3194961","pdf_url":null,"source":{"id":"https://openalex.org/S147316732","display_name":"IEEE Communications Letters","issn_l":"1089-7798","issn":["1089-7798","1558-2558","2373-7891"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310316002","host_organization_name":"IEEE Communications Society","host_organization_lineage":["https://openalex.org/P4310316002","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Communications Society","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 Communications Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.7099999785423279}],"awards":[{"id":"https://openalex.org/G1595715893","display_name":null,"funder_award_id":"B08038","funder_id":"https://openalex.org/F4320327912","funder_display_name":"Higher Education Discipline Innovation Project"},{"id":"https://openalex.org/G3067497907","display_name":"\u672a\u6765\u8702\u7a9d\u7f51\u7edc\u4e2d\u8d44\u6e90\u53d7\u9650\u6761\u4ef6\u4e0b\u5927\u89c4\u6a21MTC\u8bbe\u5907\u63a5\u5165\u673a\u5236","funder_award_id":"61901345","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3256514729","display_name":null,"funder_award_id":"61901333","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5248293312","display_name":null,"funder_award_id":"XJS220116","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G6311427012","display_name":null,"funder_award_id":"2019M663630","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"},{"id":"https://openalex.org/G7653577565","display_name":null,"funder_award_id":"62001358","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/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"},{"id":"https://openalex.org/F4320327912","display_name":"Higher Education Discipline Innovation Project","ror":null},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W64913373","https://openalex.org/W1520752838","https://openalex.org/W2009506162","https://openalex.org/W2033332370","https://openalex.org/W2054658115","https://openalex.org/W2057077708","https://openalex.org/W2096710051","https://openalex.org/W2113638573","https://openalex.org/W2116414176","https://openalex.org/W2123226256","https://openalex.org/W2142635246","https://openalex.org/W2152687999","https://openalex.org/W2155421090","https://openalex.org/W2165252709","https://openalex.org/W2166426208","https://openalex.org/W2168175751","https://openalex.org/W2767836169","https://openalex.org/W2770369314","https://openalex.org/W2784061726","https://openalex.org/W2792945424","https://openalex.org/W2980809995","https://openalex.org/W2986819504","https://openalex.org/W2993165567","https://openalex.org/W3102628653","https://openalex.org/W3124551778"],"related_works":["https://openalex.org/W2989490741","https://openalex.org/W3092506759","https://openalex.org/W2367545121","https://openalex.org/W4248881655","https://openalex.org/W2482165163","https://openalex.org/W3010890513","https://openalex.org/W120741642","https://openalex.org/W138569904","https://openalex.org/W2390914021","https://openalex.org/W2389417819"],"abstract_inverted_index":{"Source":[0],"number":[1,49],"estimation":[2,50,158],"is":[3],"an":[4],"important":[5],"problem":[6],"in":[7,15],"signal":[8,30],"processing.":[9],"The":[10,118],"performances":[11],"of":[12,62,87,95,98,114,142,155,164],"traditional":[13],"methods":[14,126],"this":[16,88,102],"field":[17],"are":[18,153],"severely":[19],"degraded":[20],"under":[21],"some":[22],"extreme":[23],"conditions,":[24],"such":[25,76],"as":[26,55,77],"relatively":[27],"short":[28],"observed":[29],"length,":[31],"low":[32],"signal-to-noise":[33],"ratio":[34],"(SNR),":[35],"or":[36],"arbitrary":[37],"noise":[38],"covariance":[39,100],"structure.":[40],"Recently,":[41],"machine":[42],"learning":[43],"has":[44,74],"been":[45],"used":[46],"for":[47],"source":[48],"with":[51],"different":[52],"data":[53,57],"formats":[54],"input":[56,112,119],"due":[58],"to":[59,108],"the":[60,92,96,99,111,115,123,133,139,143,149,157,162,165],"advantages":[61],"not":[63],"requiring":[64,81],"subjective":[65],"parameter":[66],"settings":[67],"and":[68,80],"being":[69],"data-driven.":[70],"However,":[71],"it":[72],"also":[73],"shortcomings":[75],"fluctuating":[78],"performance":[79,159],"more":[82],"training":[83],"samples.":[84],"In":[85],"view":[86],"problem,":[89],"based":[90],"on":[91],"statistical":[93],"characteristics":[94],"eigenvalues":[97],"matrix,":[101],"letter":[103],"proposes":[104],"two":[105],"preprocessing":[106,125,151],"schemes":[107,152],"further":[109],"manifest":[110],"features":[113,120],"network":[116],"model.":[117],"transformed":[121],"by":[122],"proposed":[124,150],"have":[127],"specific":[128],"distributions,":[129],"which":[130],"can":[131],"improve":[132],"discriminability":[134],"between":[135],"features,":[136],"thereby":[137],"enhancing":[138],"prediction":[140],"ability":[141],"network.":[144],"Simulation":[145],"results":[146],"verify":[147],"that":[148],"capable":[154],"improving":[156],"while":[160],"reducing":[161],"fluctuation":[163],"performance.":[166]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}