{"id":"https://openalex.org/W3141618769","doi":"https://doi.org/10.3906/elk-2005-201","title":"A deep neural network classifier for P300 BCI speller based on Cohen\u2019s class time-frequency distribution","display_name":"A deep neural network classifier for P300 BCI speller based on Cohen\u2019s class time-frequency distribution","publication_year":2020,"publication_date":"2020-11-25","ids":{"openalex":"https://openalex.org/W3141618769","doi":"https://doi.org/10.3906/elk-2005-201","mag":"3141618769"},"language":"en","primary_location":{"id":"doi:10.3906/elk-2005-201","is_oa":true,"landing_page_url":"https://doi.org/10.3906/elk-2005-201","pdf_url":"https://journals.tubitak.gov.tr/cgi/viewcontent.cgi?article=1169&context=elektrik","source":{"id":"https://openalex.org/S32837994","display_name":"TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES","issn_l":"1300-0632","issn":["1300-0632","1303-6203"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310318422","host_organization_name":"Scientific and Technological Research Council of Turkey (TUBITAK)","host_organization_lineage":["https://openalex.org/P4310318422"],"host_organization_lineage_names":["Scientific and Technological Research Council of Turkey (TUBITAK)"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://journals.tubitak.gov.tr/cgi/viewcontent.cgi?article=1169&context=elektrik","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5031354817","display_name":"Hamed Ghazikhani","orcid":"https://orcid.org/0000-0001-9587-8016"},"institutions":[{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Hamed GHAZIKHANI","raw_affiliation_strings":["Department of Computer Science and Software Engineering, Concordia University, Montreal, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Software Engineering, Concordia University, Montreal, Canada","institution_ids":["https://openalex.org/I60158472"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019671134","display_name":"Modjtaba Rouhani","orcid":"https://orcid.org/0000-0003-2423-6715"},"institutions":[{"id":"https://openalex.org/I86958956","display_name":"Ferdowsi University of Mashhad","ror":"https://ror.org/00g6ka752","country_code":"IR","type":"education","lineage":["https://openalex.org/I86958956"]}],"countries":["IR"],"is_corresponding":true,"raw_author_name":"Modjtaba ROUHANI","raw_affiliation_strings":["Department of Computer Engineering, Ferdowsi University of Mashhad (FUM), Mashhad, Iran"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Ferdowsi University of Mashhad (FUM), Mashhad, Iran","institution_ids":["https://openalex.org/I86958956"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5019671134"],"corresponding_institution_ids":["https://openalex.org/I86958956"],"apc_list":null,"apc_paid":null,"fwci":0.4404,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.61024277,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"29","issue":"2","first_page":"1226","last_page":"1240"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9987999796867371,"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":0.9987999796867371,"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/T10320","display_name":"Neural Networks and Applications","score":0.9555000066757202,"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"}},{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9534000158309937,"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/softmax-function","display_name":"Softmax function","score":0.7420191764831543},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7371187806129456},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7310394644737244},{"id":"https://openalex.org/keywords/brain\u2013computer-interface","display_name":"Brain\u2013computer interface","score":0.7310043573379517},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7091687917709351},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.570732057094574},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5572468042373657},{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.4966753125190735},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.4815695285797119},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.44532954692840576},{"id":"https://openalex.org/keywords/backpropagation","display_name":"Backpropagation","score":0.4182223081588745}],"concepts":[{"id":"https://openalex.org/C188441871","wikidata":"https://www.wikidata.org/wiki/Q7554146","display_name":"Softmax function","level":3,"score":0.7420191764831543},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7371187806129456},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7310394644737244},{"id":"https://openalex.org/C173201364","wikidata":"https://www.wikidata.org/wiki/Q897410","display_name":"Brain\u2013computer interface","level":3,"score":0.7310043573379517},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7091687917709351},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.570732057094574},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5572468042373657},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.4966753125190735},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4815695285797119},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.44532954692840576},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.4182223081588745},{"id":"https://openalex.org/C118552586","wikidata":"https://www.wikidata.org/wiki/Q7867","display_name":"Psychiatry","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3906/elk-2005-201","is_oa":true,"landing_page_url":"https://doi.org/10.3906/elk-2005-201","pdf_url":"https://journals.tubitak.gov.tr/cgi/viewcontent.cgi?article=1169&context=elektrik","source":{"id":"https://openalex.org/S32837994","display_name":"TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES","issn_l":"1300-0632","issn":["1300-0632","1303-6203"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310318422","host_organization_name":"Scientific and Technological Research Council of Turkey (TUBITAK)","host_organization_lineage":["https://openalex.org/P4310318422"],"host_organization_lineage_names":["Scientific and Technological Research Council of Turkey (TUBITAK)"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.3906/elk-2005-201","is_oa":true,"landing_page_url":"https://doi.org/10.3906/elk-2005-201","pdf_url":"https://journals.tubitak.gov.tr/cgi/viewcontent.cgi?article=1169&context=elektrik","source":{"id":"https://openalex.org/S32837994","display_name":"TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES","issn_l":"1300-0632","issn":["1300-0632","1303-6203"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310318422","host_organization_name":"Scientific and Technological Research Council of Turkey (TUBITAK)","host_organization_lineage":["https://openalex.org/P4310318422"],"host_organization_lineage_names":["Scientific and Technological Research Council of Turkey (TUBITAK)"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3141618769.pdf","grobid_xml":"https://content.openalex.org/works/W3141618769.grobid-xml"},"referenced_works_count":32,"referenced_works":["https://openalex.org/W1511019414","https://openalex.org/W1991485730","https://openalex.org/W2028798205","https://openalex.org/W2044251627","https://openalex.org/W2059016985","https://openalex.org/W2068028305","https://openalex.org/W2095737716","https://openalex.org/W2098100592","https://openalex.org/W2103450723","https://openalex.org/W2105438329","https://openalex.org/W2110545034","https://openalex.org/W2110798204","https://openalex.org/W2133062806","https://openalex.org/W2141250423","https://openalex.org/W2143058310","https://openalex.org/W2145302786","https://openalex.org/W2150590430","https://openalex.org/W2165878107","https://openalex.org/W2375202936","https://openalex.org/W2525360836","https://openalex.org/W2542991890","https://openalex.org/W2618762253","https://openalex.org/W2619528099","https://openalex.org/W2751159520","https://openalex.org/W2794345050","https://openalex.org/W2807402864","https://openalex.org/W2807662216","https://openalex.org/W2853053934","https://openalex.org/W2853982964","https://openalex.org/W2900786131","https://openalex.org/W2900868701","https://openalex.org/W4206246468"],"related_works":["https://openalex.org/W3107204728","https://openalex.org/W4287591324","https://openalex.org/W4226420367","https://openalex.org/W2980176872","https://openalex.org/W2962876041","https://openalex.org/W3090555870","https://openalex.org/W3108503355","https://openalex.org/W2947839263","https://openalex.org/W3120400911","https://openalex.org/W2106231951"],"abstract_inverted_index":{"This":[0,27,132,193],"paper":[1],"presents":[2],"a":[3,20,30,61,150,158],"new":[4],"method":[5,28],"of":[6,11,45,54,64,82,86,107,138,171],"predicting":[7],"the":[8,17,35,43,46,51,55,65,79,87,101,136,145,154,167,184],"P300":[9,21,188,201],"component":[10],"an":[12],"electroencephalography":[13],"(EEG)signal":[14],"to":[15,60,77,91,115,149],"recognize":[16],"characters":[18],"in":[19,75,186,195],"brain-computer":[22],"interface":[23],"(BCI)":[24],"speller":[25],"accurately.":[26],"consistsof":[29],"deep":[31,133],"learning":[32],"model":[33],"and":[34,49,95,109,190,197,203],"nonlinear":[36,52,80],"time-frequency":[37,105],"features.":[38,118],"It":[39],"is":[40,73,127,175],"believed":[41],"that":[42],"combination":[44],"deepmodel":[47],"network":[48,134,156],"extracting":[50,142],"features":[53,81,146],"EEG":[56],"led":[57],"this":[58,180],"research":[59],"better":[62,98],"prediction":[63],"P300and,":[66],"therefore,":[67],"character":[68,130,191,204],"recognition.":[69,131,192],"Cohen's":[70],"class":[71],"distribution":[72],"used":[74],"order":[76],"extract":[78,116],"theEEG.":[83],"Evaluating":[84],"all":[85],"kernels,":[88],"Butterworth":[89],"found":[90],"be":[92],"more":[93],"informative":[94],"it":[96],"produced":[97],"results.":[99],"Basedon":[100],"differences":[102],"observed":[103],"between":[104],"responses":[106],"target":[108],"nontarget":[110],"signals,":[111],"specific":[112],"subbands":[113],"areselected":[114],"seven":[117],"A":[119],"deep-structured":[120],"neural":[121],"network,":[122],"namely":[123],"stacked":[124],"sparse":[125],"autoencoders,":[126],"appliedfor":[128],"BCI":[129,172],"reduces":[135],"dimension":[137],"feature":[139],"space":[140],"by":[141,161],"unsupervisedfeatures.":[143],"Then,":[144],"are":[147],"fed":[148],"Softmax":[151],"classifier.":[152],"Afterward,":[153],"whole":[155],"passes":[157],"fine-tuning":[159],"phase":[160],"asupervised":[162],"backpropagation":[163],"algorithm.":[164],"For":[165],"evaluating":[166],"work,":[168],"Dataset":[169],"II":[170],"Competition":[173],"III":[174],"utilized.":[176],"Based":[177],"onthe":[178],"results,":[179],"approach":[181],"would":[182],"improve":[183],"accuracy":[185,199],"both":[187],"detection":[189],"researchresults":[194],"82.7%":[196],"93.5%":[198],"for":[200],"classification":[202],"recognition,":[205],"respectively.":[206]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2}],"updated_date":"2026-06-04T06:14:18.571774","created_date":"2025-10-10T00:00:00"}