{"id":"https://openalex.org/W2165368985","doi":"https://doi.org/10.1109/ijcnn.2011.6033202","title":"Semi-supervised feature extraction with local temporal regularization for EEG classification","display_name":"Semi-supervised feature extraction with local temporal regularization for EEG classification","publication_year":2011,"publication_date":"2011-07-01","ids":{"openalex":"https://openalex.org/W2165368985","doi":"https://doi.org/10.1109/ijcnn.2011.6033202","mag":"2165368985"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2011.6033202","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2011.6033202","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 2011 International Joint Conference on Neural Networks","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/A5056078823","display_name":"Wenting Tu","orcid":"https://orcid.org/0000-0003-1010-7189"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wenting Tu","raw_affiliation_strings":["Department of Computer Science and Technology, East China Normal University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047846625","display_name":"Shiliang Sun","orcid":"https://orcid.org/0000-0001-7069-3752"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shiliang Sun","raw_affiliation_strings":["Department of Computer Science and Technology, East China Normal University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5056078823"],"corresponding_institution_ids":["https://openalex.org/I66867065"],"apc_list":null,"apc_paid":null,"fwci":0.4121,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.63175043,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"4174","issue":null,"first_page":"75","last_page":"80"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9998000264167786,"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/T10581","display_name":"Neural dynamics and brain function","score":0.991100013256073,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.8221708536148071},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6731499433517456},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6565548181533813},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6513009071350098},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.635804295539856},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5722450017929077},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.5709264278411865},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3232232332229614},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.09587597846984863}],"concepts":[{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.8221708536148071},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6731499433517456},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6565548181533813},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6513009071350098},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.635804295539856},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5722450017929077},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.5709264278411865},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3232232332229614},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.09587597846984863}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2011.6033202","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2011.6033202","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 2011 International Joint Conference on Neural Networks","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.5799999833106995}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W206280282","https://openalex.org/W1493785539","https://openalex.org/W1565904831","https://openalex.org/W2044658366","https://openalex.org/W2104290444","https://openalex.org/W2108824330","https://openalex.org/W2108995755","https://openalex.org/W2117251170","https://openalex.org/W2141250485","https://openalex.org/W2145673887","https://openalex.org/W2154872931","https://openalex.org/W2155758585","https://openalex.org/W4248337693","https://openalex.org/W6682581627","https://openalex.org/W6682644385"],"related_works":["https://openalex.org/W4362597605","https://openalex.org/W1574414179","https://openalex.org/W4297676672","https://openalex.org/W3009056573","https://openalex.org/W2922073769","https://openalex.org/W4281702477","https://openalex.org/W3040691452","https://openalex.org/W2989932438","https://openalex.org/W4387297750","https://openalex.org/W2186333919"],"abstract_inverted_index":{"Extreme":[0],"energy":[1,124,143,163],"ratio":[2,125],"(EER)":[3],"is":[4,20,34,61],"a":[5,35,62,79,117,170,181],"recently":[6],"proposed":[7],"feature":[8,119],"extractor":[9,120],"to":[10,26,53,104,156],"learn":[11],"spatial":[12,29],"filters":[13],"for":[14],"electroencephalogram":[15],"(EEG)":[16],"signal":[17],"classification.":[18],"It":[19,89],"theoretically":[21],"equivalent":[22],"and":[23,99,192],"computationally":[24],"superior":[25],"the":[27,54,92,112,148,157,162,177,189,194],"common":[28],"patterns":[30],"(CSP)":[31],"method":[32,65],"which":[33],"widely":[36],"used":[37],"technique":[38],"in":[39],"brain-computer":[40],"interfaces":[41],"(BCIs).":[42],"However,":[43],"EER":[44,113],"may":[45],"seriously":[46],"overfit":[47],"on":[48],"small":[49],"training":[50],"sets":[51],"due":[52],"presence":[55],"of":[56,70,86,95,152,165,184,196],"large":[57],"noise.":[58],"Moreover,":[59],"it":[60],"totally":[63],"supervised":[64],"that":[66,138],"cannot":[67],"take":[68],"advantage":[69],"unlabeled":[71,87],"data.":[72],"To":[73],"overcome":[74],"these":[75,166],"limitations,":[76],"we":[77,115,186],"propose":[78],"regularization":[80,109],"constraint":[81],"utilizing":[82],"local":[83,149],"temporal":[84,93,150],"information":[85],"trails.":[88,154],"can":[90],"encourage":[91],"smoothness":[94],"source":[96,136,167],"signals":[97,137,168],"discovered,":[98],"thus":[100],"alleviate":[101],"their":[102],"tendency":[103],"overfit.":[105],"By":[106],"combining":[107],"this":[108],"trick":[110],"with":[111],"method,":[114],"present":[116,188],"semi-supervised":[118,122],"termed":[121],"extreme":[123],"(SEER).":[126],"After":[127],"solving":[128],"two":[129],"eigenvalue":[130],"decomposition":[131],"problems,":[132],"SEER":[133,191],"recovers":[134],"latent":[135],"not":[139],"only":[140],"have":[141,169],"discriminative":[142],"features":[144,158,164],"but":[145],"also":[146],"preserve":[147],"structure":[151],"test":[153],"Compared":[155],"found":[159],"by":[160,176],"EER,":[161],"stronger":[171],"generalization":[172],"ability,":[173],"as":[174],"shown":[175],"experimental":[178],"results.":[179],"As":[180],"nonlinear":[182],"extension":[183],"SEER,":[185],"further":[187],"kernel":[190],"provide":[193],"derivation":[195],"its":[197],"solutions.":[198]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2015,"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"}