{"id":"https://openalex.org/W2989184171","doi":"https://doi.org/10.1109/tnnls.2019.2944869","title":"Nonpeaked Discriminant Analysis for Data Representation","display_name":"Nonpeaked Discriminant Analysis for Data Representation","publication_year":2019,"publication_date":"2019-11-13","ids":{"openalex":"https://openalex.org/W2989184171","doi":"https://doi.org/10.1109/tnnls.2019.2944869","mag":"2989184171","pmid":"https://pubmed.ncbi.nlm.nih.gov/31725389"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2019.2944869","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2019.2944869","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5039671101","display_name":"Qiaolin Ye","orcid":"https://orcid.org/0000-0002-8793-8610"},"institutions":[{"id":"https://openalex.org/I167027274","display_name":"Nanjing Forestry University","ror":"https://ror.org/03m96p165","country_code":"CN","type":"education","lineage":["https://openalex.org/I167027274"]},{"id":"https://openalex.org/I4210128615","display_name":"Chinese Academy of Forestry","ror":"https://ror.org/0360dkv71","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210128615","https://openalex.org/I4210134523"]},{"id":"https://openalex.org/I4210114891","display_name":"Institute of Forest Resource Information Techniques","ror":"https://ror.org/01h5d6x15","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210114891","https://openalex.org/I4210128615","https://openalex.org/I4210134523"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qiaolin Ye","raw_affiliation_strings":["Chinese Academy of Forestry, Institute of Forest Resource Information Techniques, Beijing, China","College of Information Science and Technology, Nanjing Forestry University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Chinese Academy of Forestry, Institute of Forest Resource Information Techniques, Beijing, China","institution_ids":["https://openalex.org/I4210114891","https://openalex.org/I4210128615"]},{"raw_affiliation_string":"College of Information Science and Technology, Nanjing Forestry University, Nanjing, China","institution_ids":["https://openalex.org/I167027274"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017096005","display_name":"Zechao Li","orcid":"https://orcid.org/0000-0002-5341-5985"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zechao Li","raw_affiliation_strings":["College of Computer Science and Technology, Nanjing University of Science and Technology, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Nanjing University of Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087729203","display_name":"Liyong Fu","orcid":"https://orcid.org/0000-0002-5794-9458"},"institutions":[{"id":"https://openalex.org/I4210114891","display_name":"Institute of Forest Resource Information Techniques","ror":"https://ror.org/01h5d6x15","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210114891","https://openalex.org/I4210128615","https://openalex.org/I4210134523"]},{"id":"https://openalex.org/I4210128615","display_name":"Chinese Academy of Forestry","ror":"https://ror.org/0360dkv71","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210128615","https://openalex.org/I4210134523"]},{"id":"https://openalex.org/I4210134523","display_name":"State Forestry and Grassland Administration","ror":"https://ror.org/03f2n3n81","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210134523"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liyong Fu","raw_affiliation_strings":["Chinese Academy of Forestry, Institute of Forest Resource Information Techniques, Beijing, China","Key Laboratory of Forest Management and Growth Modeling, National Forestry and Grassland Administration, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Chinese Academy of Forestry, Institute of Forest Resource Information Techniques, Beijing, China","institution_ids":["https://openalex.org/I4210114891","https://openalex.org/I4210128615"]},{"raw_affiliation_string":"Key Laboratory of Forest Management and Growth Modeling, National Forestry and Grassland Administration, Beijing, China","institution_ids":["https://openalex.org/I4210134523"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100423029","display_name":"Zhao Zhang","orcid":"https://orcid.org/0000-0002-5703-7969"},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]},{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhao Zhang","raw_affiliation_strings":["School of Computer Science and Technology, Soochow University, Suzhou, China","School of Computer and Information, Hefei University of Technology, Hefei, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Soochow University, Suzhou, China","institution_ids":["https://openalex.org/I3923682"]},{"raw_affiliation_string":"School of Computer and Information, Hefei University of Technology, Hefei, China","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100748706","display_name":"Wankou Yang","orcid":"https://orcid.org/0000-0002-6385-6776"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wankou Yang","raw_affiliation_strings":["School of Automation, Southeast University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"School of Automation, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037953083","display_name":"Guowei Yang","orcid":"https://orcid.org/0000-0002-5204-1766"},"institutions":[{"id":"https://openalex.org/I206777745","display_name":"Nanjing Audit University","ror":"https://ror.org/04zj2bd87","country_code":"CN","type":"education","lineage":["https://openalex.org/I206777745"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guowei Yang","raw_affiliation_strings":["Jiangsu Key Laboratory of Auditing Information Engineering, Nanjing Audit University, Nanjing, China","School of Information Engineering, Nanjing Audit University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Jiangsu Key Laboratory of Auditing Information Engineering, Nanjing Audit University, Nanjing, China","institution_ids":["https://openalex.org/I206777745"]},{"raw_affiliation_string":"School of Information Engineering, Nanjing Audit University, Nanjing, China","institution_ids":["https://openalex.org/I206777745"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5039671101"],"corresponding_institution_ids":["https://openalex.org/I167027274","https://openalex.org/I4210114891","https://openalex.org/I4210128615"],"apc_list":null,"apc_paid":null,"fwci":8.7052,"has_fulltext":false,"cited_by_count":118,"citation_normalized_percentile":{"value":0.9823816,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"30","issue":"12","first_page":"3818","last_page":"3832"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9990000128746033,"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"}},"topics":[{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9990000128746033,"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"}},{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9861999750137329,"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/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"}}],"keywords":[{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.6935617327690125},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.6790473461151123},{"id":"https://openalex.org/keywords/discriminant","display_name":"Discriminant","score":0.6219562888145447},{"id":"https://openalex.org/keywords/norm","display_name":"Norm (philosophy)","score":0.5950812697410583},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4893342852592468},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.48806512355804443},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47823280096054077},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4669885039329529},{"id":"https://openalex.org/keywords/matrix-norm","display_name":"Matrix norm","score":0.45563071966171265},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4078708589076996},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.38731029629707336},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3281986117362976},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.09558704495429993}],"concepts":[{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.6935617327690125},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.6790473461151123},{"id":"https://openalex.org/C78397625","wikidata":"https://www.wikidata.org/wiki/Q192487","display_name":"Discriminant","level":2,"score":0.6219562888145447},{"id":"https://openalex.org/C191795146","wikidata":"https://www.wikidata.org/wiki/Q3878446","display_name":"Norm (philosophy)","level":2,"score":0.5950812697410583},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4893342852592468},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.48806512355804443},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47823280096054077},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4669885039329529},{"id":"https://openalex.org/C92207270","wikidata":"https://www.wikidata.org/wiki/Q939253","display_name":"Matrix norm","level":3,"score":0.45563071966171265},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4078708589076996},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.38731029629707336},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3281986117362976},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.09558704495429993},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","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/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"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":2,"locations":[{"id":"doi:10.1109/tnnls.2019.2944869","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2019.2944869","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:31725389","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/31725389","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7099999785423279,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G1000548808","display_name":null,"funder_award_id":"61871444","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4298815191","display_name":null,"funder_award_id":"BK20171453","funder_id":"https://openalex.org/F4320322769","funder_display_name":"Natural Science Foundation of Jiangsu Province"},{"id":"https://openalex.org/G5438267384","display_name":null,"funder_award_id":"BK20170033","funder_id":"https://openalex.org/F4320322769","funder_display_name":"Natural Science Foundation of Jiangsu Province"},{"id":"https://openalex.org/G6631301308","display_name":null,"funder_award_id":"2017YFC0820601","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program 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/F4320322769","display_name":"Natural Science Foundation of Jiangsu Province","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320326182","display_name":"Six Talent Peaks Project in Jiangsu Province","ror":null},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":62,"referenced_works":["https://openalex.org/W147992333","https://openalex.org/W1166921479","https://openalex.org/W1979714579","https://openalex.org/W1992633833","https://openalex.org/W2002427601","https://openalex.org/W2005347517","https://openalex.org/W2008277111","https://openalex.org/W2042970394","https://openalex.org/W2053090063","https://openalex.org/W2056935845","https://openalex.org/W2076019763","https://openalex.org/W2098004870","https://openalex.org/W2100495367","https://openalex.org/W2101117936","https://openalex.org/W2109531142","https://openalex.org/W2117553576","https://openalex.org/W2125874614","https://openalex.org/W2133538634","https://openalex.org/W2135081536","https://openalex.org/W2138451337","https://openalex.org/W2145862222","https://openalex.org/W2151416140","https://openalex.org/W2157032359","https://openalex.org/W2163376981","https://openalex.org/W2166693468","https://openalex.org/W2171188027","https://openalex.org/W2171837816","https://openalex.org/W2240559667","https://openalex.org/W2297991835","https://openalex.org/W2337719340","https://openalex.org/W2343830850","https://openalex.org/W2398274324","https://openalex.org/W2401764675","https://openalex.org/W2428936319","https://openalex.org/W2464913182","https://openalex.org/W2466114631","https://openalex.org/W2472885885","https://openalex.org/W2516176725","https://openalex.org/W2543969232","https://openalex.org/W2565703388","https://openalex.org/W2604827371","https://openalex.org/W2607323999","https://openalex.org/W2608501919","https://openalex.org/W2699934687","https://openalex.org/W2742001166","https://openalex.org/W2754803257","https://openalex.org/W2761818166","https://openalex.org/W2769417998","https://openalex.org/W2793544474","https://openalex.org/W2794268568","https://openalex.org/W2807548733","https://openalex.org/W2889400998","https://openalex.org/W3014771378","https://openalex.org/W3023553797","https://openalex.org/W3104195492","https://openalex.org/W3120740533","https://openalex.org/W3148981562","https://openalex.org/W4250589301","https://openalex.org/W6605914596","https://openalex.org/W6676189307","https://openalex.org/W6682205712","https://openalex.org/W6786499053"],"related_works":["https://openalex.org/W2350751952","https://openalex.org/W1999647744","https://openalex.org/W2362114017","https://openalex.org/W3147024994","https://openalex.org/W2063246903","https://openalex.org/W2374055396","https://openalex.org/W1978302214","https://openalex.org/W2021817983","https://openalex.org/W2104382484","https://openalex.org/W3008559849"],"abstract_inverted_index":{"Of":[0],"late,":[1],"there":[2],"are":[3,21,92,149,160],"many":[4],"studies":[5],"on":[6,94,143,165],"the":[7,15,33,52,68,85,95,118,135,138,144,147,157],"robust":[8,23,87],"discriminant":[9,41,88],"analysis,":[10],"which":[11,46,91],"adopt":[12],"L<sub>1</sub>-norm":[13,48,96,110],"as":[14,51],"distance":[16,53,97,111],"metric,":[17],"but":[18],"their":[19],"results":[20],"not":[22],"enough":[24],"to":[25,73,106],"gain":[26],"universal":[27],"acceptance.":[28],"To":[29],"overcome":[30],"this":[31,36,56,126],"problem,":[32],"authors":[34,100],"of":[35,58,137,146,156],"article":[37],"present":[38,102],"a":[39,103],"nonpeaked":[40],"analysis":[42,89,105],"(NPDA)":[43],"technique,":[44],"in":[45,65,76],"cutting":[47,109],"is":[49,71,132],"adopted":[50],"metric.":[54,98],"As":[55],"kind":[57],"norm":[59],"can":[60,112],"better":[61],"eliminate":[62],"heavy":[63],"outliers":[64],"learning":[66],"models,":[67],"proposed":[69,139,158],"algorithm":[70,131,148],"expected":[72],"be":[74,113],"stronger":[75],"performing":[77],"feature":[78],"extraction":[79],"tasks":[80],"for":[81,134],"data":[82,168],"representation":[83],"than":[84],"existing":[86],"techniques,":[90],"based":[93],"The":[99],"also":[101,150],"comprehensive":[104],"show":[107],"that":[108],"computed":[114],"equally":[115],"well,":[116],"using":[117],"difference":[119],"between":[120],"two":[121],"special":[122],"convex":[123],"functions.":[124],"Against":[125],"background,":[127],"an":[128],"efficient":[129],"iterative":[130],"designed":[133],"optimization":[136],"objective.":[140],"Theoretical":[141,152],"proofs":[142],"convergence":[145],"presented.":[151],"insights":[153],"and":[154],"effectiveness":[155],"method":[159],"validated":[161],"by":[162],"experimental":[163],"tests":[164],"several":[166],"real":[167],"sets.":[169]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":21},{"year":2022,"cited_by_count":46},{"year":2021,"cited_by_count":29},{"year":2020,"cited_by_count":10},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
