{"id":"https://openalex.org/W2538707956","doi":"https://doi.org/10.1109/iccchina.2016.7636897","title":"An EEG signal classification method based on sparse auto-encoders and support vector machine","display_name":"An EEG signal classification method based on sparse auto-encoders and support vector machine","publication_year":2016,"publication_date":"2016-07-01","ids":{"openalex":"https://openalex.org/W2538707956","doi":"https://doi.org/10.1109/iccchina.2016.7636897","mag":"2538707956"},"language":"en","primary_location":{"id":"doi:10.1109/iccchina.2016.7636897","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccchina.2016.7636897","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE/CIC International Conference on Communications in China (ICCC)","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/A5110951538","display_name":"Bo Yan","orcid":"https://orcid.org/0000-0003-1750-3803"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Bo Yan","raw_affiliation_strings":["School of Communication & Information Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"School of Communication & Information Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100424542","display_name":"Yong Wang","orcid":"https://orcid.org/0000-0003-3366-3137"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yong Wang","raw_affiliation_strings":["School of Communication & Information Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"School of Communication & Information Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100652797","display_name":"Yuheng Li","orcid":"https://orcid.org/0009-0001-0249-8952"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuheng Li","raw_affiliation_strings":["School of Communication & Information Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"School of Communication & Information Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083367593","display_name":"Yejiang Gong","orcid":null},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yejiang Gong","raw_affiliation_strings":["School of Communication & Information Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"School of Communication & Information Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064816543","display_name":"Lu Guan","orcid":"https://orcid.org/0000-0002-9309-2834"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lu Guan","raw_affiliation_strings":["School of Communication & Information Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"School of Communication & Information Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004259273","display_name":"Sheng Yu","orcid":"https://orcid.org/0009-0008-3460-0772"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sheng Yu","raw_affiliation_strings":["Sichuan Jingyi Anti-Counterfeiting Technology Ltd., Chengdu, China"],"affiliations":[{"raw_affiliation_string":"Sichuan Jingyi Anti-Counterfeiting Technology Ltd., Chengdu, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5110951538"],"corresponding_institution_ids":["https://openalex.org/I150229711"],"apc_list":null,"apc_paid":null,"fwci":1.1659,"has_fulltext":false,"cited_by_count":23,"citation_normalized_percentile":{"value":0.78285022,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9993000030517578,"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/T11601","display_name":"Neuroscience and Neural Engineering","score":0.9940000176429749,"subfield":{"id":"https://openalex.org/subfields/2804","display_name":"Cellular and Molecular 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/support-vector-machine","display_name":"Support vector machine","score":0.80777508020401},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7675695419311523},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7064098119735718},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6575309038162231},{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.5780788660049438},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5077117681503296},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.47418293356895447},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.43826979398727417},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3948506712913513},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.19919434189796448}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.80777508020401},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7675695419311523},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7064098119735718},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6575309038162231},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.5780788660049438},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5077117681503296},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.47418293356895447},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.43826979398727417},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3948506712913513},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.19919434189796448},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"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},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccchina.2016.7636897","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccchina.2016.7636897","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE/CIC International Conference on Communications in China (ICCC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","score":0.46000000834465027,"display_name":"Good health and well-being"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1972653561","https://openalex.org/W2003875143","https://openalex.org/W2059016985","https://openalex.org/W2074798134","https://openalex.org/W2080146971","https://openalex.org/W2081895431","https://openalex.org/W2098120923","https://openalex.org/W2105728138","https://openalex.org/W2105923830","https://openalex.org/W2119269525","https://openalex.org/W2140434576","https://openalex.org/W2164452299","https://openalex.org/W6675897241"],"related_works":["https://openalex.org/W2922348724","https://openalex.org/W200322357","https://openalex.org/W2130428257","https://openalex.org/W4308951944","https://openalex.org/W2057366091","https://openalex.org/W2049513647","https://openalex.org/W2090763504","https://openalex.org/W2988848585","https://openalex.org/W4233722919","https://openalex.org/W4390516098"],"abstract_inverted_index":{"EEG":[0,20,97,151,178],"signals,":[1,98],"recording":[2],"abnormal":[3],"discharge":[4],"of":[5,46,96],"neurons":[6],"in":[7,13,124,135,171],"the":[8,39,44,47,58,85,92,101,120,125,150,158,168,175],"brain,":[9],"are":[10],"widely":[11,76],"used":[12,77,89,155],"epilepsy":[14],"detection.":[15,49],"In":[16,50,141],"this":[17,172],"paper,":[18],"an":[19],"signal":[21],"classification":[22,133,146,161,169],"method":[23],"based":[24],"on":[25],"sparse":[26,53,107],"auto-encoders":[27],"(SAE)":[28],"and":[29,42,99,128],"support":[30],"vector":[31],"machine":[32],"(SVM)":[33],"is":[34,75,88,111,154],"proposed":[35],"to":[36,72,78,90,114,137,143,156],"greatly":[37],"reduce":[38],"sample":[40,63],"rate":[41,64],"enhance":[43],"efficiency":[45],"vision":[48],"practical":[51],"application,":[52],"auto-encoder":[54],"can":[55],"get":[56],"all":[57],"significant":[59],"information":[60,95],"at":[61],"lower":[62],"than":[65,119],"sampled":[66],"by":[67],"Nyquist":[68],"sampling":[69,116],"principle.":[70],"Due":[71],"this,":[73],"it":[74,87],"extract":[79],"higher":[80],"layer":[81],"features":[82],"automatically.":[83],"With":[84],"latter,":[86],"obtain":[91],"high-dimensional":[93],"pattern":[94],"map":[100],"input":[102],"mode":[103],"space":[104],"into":[105],"corresponding":[106],"space.":[108],"This":[109],"approach":[110],"precise":[112],"enough":[113],"each":[115],"point":[117],"rather":[118],"conventional":[121,139],"time":[122],"window":[123],"current":[126,176],"researches":[127],"also":[129],"has":[130],"a":[131],"better":[132],"speed":[134],"comparison":[136],"other":[138],"methods.":[140,181],"order":[142],"ensure":[144],"good":[145],"rates":[147,170],"(100%)":[148],"for":[149],"database,":[152],"SVM":[153],"construct":[157],"generalized":[159],"optimal":[160],"hyper":[162],"plane.":[163],"Experimental":[164],"result":[165],"demonstrate":[166],"that":[167],"work":[173],"outperform":[174],"state-of-the-art":[177],"seizure":[179],"detection":[180]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":1}],"updated_date":"2026-03-28T08:17:26.163206","created_date":"2025-10-10T00:00:00"}