{"id":"https://openalex.org/W2016549004","doi":"https://doi.org/10.1109/prni.2014.6858523","title":"Mean shrinkage improves the classification of ERP signals by exploiting additional label information","display_name":"Mean shrinkage improves the classification of ERP signals by exploiting additional label information","publication_year":2014,"publication_date":"2014-06-01","ids":{"openalex":"https://openalex.org/W2016549004","doi":"https://doi.org/10.1109/prni.2014.6858523","mag":"2016549004"},"language":"en","primary_location":{"id":"doi:10.1109/prni.2014.6858523","is_oa":false,"landing_page_url":"https://doi.org/10.1109/prni.2014.6858523","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 International Workshop on Pattern Recognition in Neuroimaging","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/A5084731010","display_name":"Johannes H\u00f6hne","orcid":null},"institutions":[{"id":"https://openalex.org/I4577782","display_name":"Technische Universit\u00e4t Berlin","ror":"https://ror.org/03v4gjf40","country_code":"DE","type":"education","lineage":["https://openalex.org/I4577782"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Johannes Hohne","raw_affiliation_strings":["Technische Universitat Berlin, Berlin, Berlin, DE","Neurotechnology group, Berlin Inst. of Technol., Berlin, Germany"],"affiliations":[{"raw_affiliation_string":"Technische Universitat Berlin, Berlin, Berlin, DE","institution_ids":["https://openalex.org/I4577782"]},{"raw_affiliation_string":"Neurotechnology group, Berlin Inst. of Technol., Berlin, Germany","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060955050","display_name":"Benjamin Blankertz","orcid":"https://orcid.org/0000-0002-2437-4846"},"institutions":[{"id":"https://openalex.org/I4577782","display_name":"Technische Universit\u00e4t Berlin","ror":"https://ror.org/03v4gjf40","country_code":"DE","type":"education","lineage":["https://openalex.org/I4577782"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Benjamin Blankertz","raw_affiliation_strings":["Technische Universitat Berlin, Berlin, Berlin, DE","Neurotechnology group, Berlin Inst. of Technol., Berlin, Germany"],"affiliations":[{"raw_affiliation_string":"Technische Universitat Berlin, Berlin, Berlin, DE","institution_ids":["https://openalex.org/I4577782"]},{"raw_affiliation_string":"Neurotechnology group, Berlin Inst. of Technol., Berlin, Germany","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107838719","display_name":"Klaus\u2010Robert M\u00fcller","orcid":null},"institutions":[{"id":"https://openalex.org/I4210148503","display_name":"Fraunhofer Institute for Production Systems and Design Technology","ror":"https://ror.org/045eg9c12","country_code":"DE","type":"facility","lineage":["https://openalex.org/I4210148503","https://openalex.org/I4923324"]},{"id":"https://openalex.org/I4577782","display_name":"Technische Universit\u00e4t Berlin","ror":"https://ror.org/03v4gjf40","country_code":"DE","type":"education","lineage":["https://openalex.org/I4577782"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Klaus-Robert Muller","raw_affiliation_strings":["Technische Universitat Berlin, Berlin, Berlin, DE","Dept. of Machine Learning, Berlin Inst. of Technol., Berlin, Germany"],"affiliations":[{"raw_affiliation_string":"Technische Universitat Berlin, Berlin, Berlin, DE","institution_ids":["https://openalex.org/I4577782"]},{"raw_affiliation_string":"Dept. of Machine Learning, Berlin Inst. of Technol., Berlin, Germany","institution_ids":["https://openalex.org/I4210148503"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074247902","display_name":"Daniel Bartz","orcid":null},"institutions":[{"id":"https://openalex.org/I4577782","display_name":"Technische Universit\u00e4t Berlin","ror":"https://ror.org/03v4gjf40","country_code":"DE","type":"education","lineage":["https://openalex.org/I4577782"]},{"id":"https://openalex.org/I4210148503","display_name":"Fraunhofer Institute for Production Systems and Design Technology","ror":"https://ror.org/045eg9c12","country_code":"DE","type":"facility","lineage":["https://openalex.org/I4210148503","https://openalex.org/I4923324"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Daniel Bartz","raw_affiliation_strings":["Technische Universitat Berlin, Berlin, Berlin, DE","Dept. of Machine Learning, Berlin Inst. of Technol., Berlin, Germany"],"affiliations":[{"raw_affiliation_string":"Technische Universitat Berlin, Berlin, Berlin, DE","institution_ids":["https://openalex.org/I4577782"]},{"raw_affiliation_string":"Dept. of Machine Learning, Berlin Inst. of Technol., Berlin, Germany","institution_ids":["https://openalex.org/I4210148503"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5084731010"],"corresponding_institution_ids":["https://openalex.org/I4577782"],"apc_list":null,"apc_paid":null,"fwci":0.7656,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.69417038,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"1","issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":1.0,"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":1.0,"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/T10581","display_name":"Neural dynamics and brain function","score":0.9945999979972839,"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":0.9940000176429749,"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/computer-science","display_name":"Computer science","score":0.750813364982605},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.7215977907180786},{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.6327430009841919},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6306604743003845},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.591610312461853},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5243985056877136},{"id":"https://openalex.org/keywords/discriminant","display_name":"Discriminant","score":0.46789395809173584},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.36314961314201355}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.750813364982605},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.7215977907180786},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.6327430009841919},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6306604743003845},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.591610312461853},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5243985056877136},{"id":"https://openalex.org/C78397625","wikidata":"https://www.wikidata.org/wiki/Q192487","display_name":"Discriminant","level":2,"score":0.46789395809173584},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36314961314201355},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/prni.2014.6858523","is_oa":false,"landing_page_url":"https://doi.org/10.1109/prni.2014.6858523","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 International Workshop on Pattern Recognition in Neuroimaging","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.7400000095367432}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1584444527","https://openalex.org/W1967167074","https://openalex.org/W1969715890","https://openalex.org/W1980381399","https://openalex.org/W2004584853","https://openalex.org/W2018034156","https://openalex.org/W2046143942","https://openalex.org/W2046709760","https://openalex.org/W2062125287","https://openalex.org/W2072735345","https://openalex.org/W2075647286","https://openalex.org/W2098735891","https://openalex.org/W2118047803","https://openalex.org/W2152171700","https://openalex.org/W2498264865","https://openalex.org/W6634927326","https://openalex.org/W6677543479"],"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/W3008559849","https://openalex.org/W2371177901"],"abstract_inverted_index":{"Linear":[0],"discriminant":[1],"analysis":[2],"(LDA)":[3],"is":[4,38,50],"the":[5,34,62,68,75,124],"most":[6],"commonly":[7],"used":[8],"classification":[9,99],"method":[10],"for":[11],"single":[12],"trial":[13],"data":[14,53,115],"in":[15,52],"a":[16,97,110],"brain-computer":[17],"interface":[18],"(BCI)":[19],"framework.":[20],"The":[21],"popularity":[22],"of":[23,67,112],"LDA":[24,36,126],"arises":[25],"from":[26,54,91],"its":[27],"robustness,":[28],"simplicity":[29],"and":[30,71,83],"high":[31],"accuracy.":[32],"However,":[33],"standard":[35,125],"approach":[37,100,122],"not":[39],"capable":[40],"to":[41],"exploit":[42],"sublabel":[43],"information":[44],"(such":[45],"as":[46],"stimulus":[47,69],"identity),":[48],"which":[49,87,101],"accessible":[51],"event":[55],"related":[56],"potentials":[57,64],"(ERPs):":[58],"it":[59],"assumes":[60],"that":[61,119],"evoked":[63],"are":[65],"independent":[66],"identity":[70],"dependent":[72],"only":[73],"on":[74,109],"users'":[76],"attentional":[77],"state.":[78],"We":[79],"question":[80],"this":[81],"assumption":[82],"investigate":[84],"several":[85],"methods":[86],"extract":[88],"subclass-specific":[89,103],"features":[90,104],"ERP":[92],"data.":[93],"Moreover,":[94],"we":[95,117],"propose":[96],"novel":[98,121],"exploits":[102],"using":[105],"mean":[106],"shrinkage.":[107],"Based":[108],"reanalysis":[111],"two":[113],"BCI":[114],"sets,":[116],"show":[118],"our":[120],"outperforms":[123],"approach,":[127],"while":[128],"being":[129],"computationally":[130],"highly":[131],"efficient.":[132]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}