{"id":"https://openalex.org/W3090735426","doi":"https://doi.org/10.1109/ijcnn48605.2020.9207236","title":"Deep Spiking Neural Network Using Spatio-temporal Backpropagation with Variable Resistance","display_name":"Deep Spiking Neural Network Using Spatio-temporal Backpropagation with Variable Resistance","publication_year":2020,"publication_date":"2020-07-01","ids":{"openalex":"https://openalex.org/W3090735426","doi":"https://doi.org/10.1109/ijcnn48605.2020.9207236","mag":"3090735426"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn48605.2020.9207236","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn48605.2020.9207236","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5086311967","display_name":"Xianglan Wen","orcid":null},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]},{"id":"https://openalex.org/I4210125143","display_name":"Chengdu University","ror":"https://ror.org/034z67559","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210125143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xianglan Wen","raw_affiliation_strings":["College of Computer Science, Sichuan University, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science, Sichuan University, Chengdu, China","institution_ids":["https://openalex.org/I4210125143","https://openalex.org/I24185976"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015742040","display_name":"Pengjie Gu","orcid":null},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]},{"id":"https://openalex.org/I4210125143","display_name":"Chengdu University","ror":"https://ror.org/034z67559","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210125143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pengjie Gu","raw_affiliation_strings":["College of Computer Science, Sichuan University, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science, Sichuan University, Chengdu, China","institution_ids":["https://openalex.org/I4210125143","https://openalex.org/I24185976"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046836420","display_name":"Rui Yan","orcid":"https://orcid.org/0000-0003-0048-3092"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]},{"id":"https://openalex.org/I4210125143","display_name":"Chengdu University","ror":"https://ror.org/034z67559","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210125143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rui Yan","raw_affiliation_strings":["College of Computer Science, Sichuan University, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science, Sichuan University, Chengdu, China","institution_ids":["https://openalex.org/I4210125143","https://openalex.org/I24185976"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057282687","display_name":"Huajin Tang","orcid":"https://orcid.org/0000-0002-9857-1543"},"institutions":[{"id":"https://openalex.org/I55712492","display_name":"Zhejiang University of Technology","ror":"https://ror.org/02djqfd08","country_code":"CN","type":"education","lineage":["https://openalex.org/I55712492"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huajin Tang","raw_affiliation_strings":["College of Computer Science, Zhejiang University of Technology, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science, Zhejiang University of Technology, Hangzhou, China","institution_ids":["https://openalex.org/I55712492"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"14","issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T10581","display_name":"Neural dynamics and brain function","score":0.9988999962806702,"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/T11601","display_name":"Neuroscience and Neural Engineering","score":0.9958000183105469,"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/computer-science","display_name":"Computer science","score":0.7688614726066589},{"id":"https://openalex.org/keywords/biological-neuron-model","display_name":"Biological neuron model","score":0.7460965514183044},{"id":"https://openalex.org/keywords/spiking-neural-network","display_name":"Spiking neural network","score":0.7197065353393555},{"id":"https://openalex.org/keywords/variable","display_name":"Variable (mathematics)","score":0.6697965264320374},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6495957374572754},{"id":"https://openalex.org/keywords/backpropagation","display_name":"Backpropagation","score":0.6273572444915771},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6187943816184998},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.48617929220199585},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.44383111596107483},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3808201253414154},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09488147497177124}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7688614726066589},{"id":"https://openalex.org/C186565885","wikidata":"https://www.wikidata.org/wiki/Q1651163","display_name":"Biological neuron model","level":3,"score":0.7460965514183044},{"id":"https://openalex.org/C11731999","wikidata":"https://www.wikidata.org/wiki/Q9067355","display_name":"Spiking neural network","level":3,"score":0.7197065353393555},{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.6697965264320374},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6495957374572754},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.6273572444915771},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6187943816184998},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.48617929220199585},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.44383111596107483},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3808201253414154},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09488147497177124},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn48605.2020.9207236","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn48605.2020.9207236","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W30445584","https://openalex.org/W345956458","https://openalex.org/W1645800954","https://openalex.org/W1970109917","https://openalex.org/W1985940938","https://openalex.org/W1987994242","https://openalex.org/W1990118406","https://openalex.org/W2008008156","https://openalex.org/W2109596721","https://openalex.org/W2110007838","https://openalex.org/W2115831804","https://openalex.org/W2120077739","https://openalex.org/W2130459697","https://openalex.org/W2130974072","https://openalex.org/W2138913040","https://openalex.org/W2154611643","https://openalex.org/W2164653071","https://openalex.org/W2171236529","https://openalex.org/W2233731247","https://openalex.org/W2290982066","https://openalex.org/W2296724634","https://openalex.org/W2440756100","https://openalex.org/W2513853720","https://openalex.org/W2569813014","https://openalex.org/W2579313944","https://openalex.org/W2604509013","https://openalex.org/W2621826044","https://openalex.org/W2745933219","https://openalex.org/W2775079417","https://openalex.org/W2779025322","https://openalex.org/W2802748234","https://openalex.org/W2808518417","https://openalex.org/W2891530223","https://openalex.org/W2891970965","https://openalex.org/W2966400611","https://openalex.org/W2966513546","https://openalex.org/W2967417697","https://openalex.org/W2976176360","https://openalex.org/W3043133474","https://openalex.org/W4238614602","https://openalex.org/W6689286705","https://openalex.org/W6697040288","https://openalex.org/W6754595668","https://openalex.org/W6766501117"],"related_works":["https://openalex.org/W2023492997","https://openalex.org/W2013860114","https://openalex.org/W1504796302","https://openalex.org/W2984834157","https://openalex.org/W2906832317","https://openalex.org/W3158152643","https://openalex.org/W2996874253","https://openalex.org/W4380324631","https://openalex.org/W3212279325","https://openalex.org/W2088600489"],"abstract_inverted_index":{"In":[0,65],"recent":[1],"years,":[2],"the":[3,57,63,70,98,101,110,133,147,151,156,159,162,166,170,176],"learning":[4,119],"of":[5,100,109,150,158],"deep":[6,49],"spiking":[7],"neural":[8],"networks(SNN)":[9],"has":[10,16],"attracted":[11],"increasing":[12],"researchers'":[13],"interest,":[14],"and":[15,23,36,51,138,169],"also":[17],"made":[18],"important":[19],"progresses":[20],"in":[21,48,62],"theories":[22],"applications.":[24],"It":[25],"is":[26,45,81,95],"desired":[27],"to":[28,97],"choose":[29],"a":[30,116,128],"neuron":[31,78,93,103,152],"model":[32,44,86,94,153],"with":[33,87],"biological":[34,102],"features":[35],"suitable":[37],"for":[38],"SNN":[39,50,118],"training.":[40],"Currently,":[41],"Leaky":[42],"Integrate-and-Fire(LIF)":[43],"mainly":[46],"used":[47],"some":[52],"factors":[53],"that":[54,121,146],"can":[55,106,173],"express":[56],"spatio-temporal":[58,111,123],"information":[59],"are":[60],"ignored":[61],"model.":[64,160],"this":[66],"work,":[67],"inspired":[68],"by":[69,126],"Hodgkin-Huxley(H-H)":[71],"model,":[72,79,104],"we":[73],"propose":[74],"an":[75,82],"improved":[76,92],"LIF":[77,85],"which":[80,105],"iterative":[83],"current-based":[84],"voltage-based":[88],"variable":[89,148,167],"resistance.":[90],"The":[91,142],"closer":[96],"characteristics":[99],"make":[107],"use":[108],"information.":[112],"We":[113,131],"further":[114],"construct":[115],"new":[117],"algorithm":[120],"uses":[122],"back":[124],"propagation":[125],"defining":[127],"loss":[129],"function.":[130],"evaluated":[132],"proposed":[134],"methods":[135],"on":[136],"single-label":[137],"multi-label":[139],"data":[140],"sets.":[141],"experimental":[143],"results":[144],"show":[145],"resistance":[149,168],"will":[154],"affect":[155],"performance":[157],"Choosing":[161],"appropriate":[163],"relationship":[164],"between":[165],"membrane":[171],"voltage":[172],"effectively":[174],"improve":[175],"recognition":[177],"accuracy.":[178]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}