{"id":"https://openalex.org/W4407231212","doi":"https://doi.org/10.1109/icta64028.2024.10860552","title":"Energy-Efficient and Fault-Tolerant Sparse Coding for Spiking Neural Networks Accelerator","display_name":"Energy-Efficient and Fault-Tolerant Sparse Coding for Spiking Neural Networks Accelerator","publication_year":2024,"publication_date":"2024-10-25","ids":{"openalex":"https://openalex.org/W4407231212","doi":"https://doi.org/10.1109/icta64028.2024.10860552"},"language":"en","primary_location":{"id":"doi:10.1109/icta64028.2024.10860552","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icta64028.2024.10860552","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Integrated Circuits, Technologies and Applications (ICTA)","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/A5101668875","display_name":"Bo Li","orcid":"https://orcid.org/0009-0006-5102-4047"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Li","raw_affiliation_strings":["Sun Yat-sen University,School of Microelectronics Science and Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University,School of Microelectronics Science and Technology","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062908102","display_name":"Wei Liu","orcid":"https://orcid.org/0000-0003-2968-2888"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Liu","raw_affiliation_strings":["Sun Yat-sen University,School of Microelectronics Science and Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University,School of Microelectronics Science and Technology","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114734399","display_name":"Yue Liu","orcid":"https://orcid.org/0009-0003-6887-8282"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yue Liu","raw_affiliation_strings":["Sun Yat-sen University,School of Microelectronics Science and Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University,School of Microelectronics Science and Technology","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Xiao Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiao Huang","raw_affiliation_strings":["Sun Yat-sen University,School of Microelectronics Science and Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University,School of Microelectronics Science and Technology","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017560036","display_name":"Zhiyi Yu","orcid":"https://orcid.org/0000-0002-8802-0457"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiyi Yu","raw_affiliation_strings":["Sun Yat-sen University,School of Microelectronics Science and Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University,School of Microelectronics Science and Technology","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079537451","display_name":"Shanlin Xiao","orcid":"https://orcid.org/0000-0002-1250-8704"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shanlin Xiao","raw_affiliation_strings":["Sun Yat-sen University,School of Microelectronics Science and Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University,School of Microelectronics Science and Technology","institution_ids":["https://openalex.org/I157773358"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I157773358"],"apc_list":null,"apc_paid":null,"fwci":0.1816,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.54093635,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"47","last_page":"48"},"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/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.9958000183105469,"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/T11601","display_name":"Neuroscience and Neural Engineering","score":0.9922000169754028,"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":0.7230169773101807},{"id":"https://openalex.org/keywords/neural-coding","display_name":"Neural coding","score":0.694385826587677},{"id":"https://openalex.org/keywords/fault-tolerance","display_name":"Fault tolerance","score":0.6620278358459473},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5519227981567383},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.5416043996810913},{"id":"https://openalex.org/keywords/spiking-neural-network","display_name":"Spiking neural network","score":0.506555438041687},{"id":"https://openalex.org/keywords/efficient-energy-use","display_name":"Efficient energy use","score":0.4483095109462738},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.4241068363189697},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.31178608536720276},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.2010103464126587},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.14671123027801514},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.14274775981903076},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.09435522556304932}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7230169773101807},{"id":"https://openalex.org/C77637269","wikidata":"https://www.wikidata.org/wiki/Q7002051","display_name":"Neural coding","level":2,"score":0.694385826587677},{"id":"https://openalex.org/C63540848","wikidata":"https://www.wikidata.org/wiki/Q3140932","display_name":"Fault tolerance","level":2,"score":0.6620278358459473},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5519227981567383},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.5416043996810913},{"id":"https://openalex.org/C11731999","wikidata":"https://www.wikidata.org/wiki/Q9067355","display_name":"Spiking neural network","level":3,"score":0.506555438041687},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.4483095109462738},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.4241068363189697},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.31178608536720276},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.2010103464126587},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.14671123027801514},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.14274775981903076},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.09435522556304932},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icta64028.2024.10860552","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icta64028.2024.10860552","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Integrated Circuits, Technologies and Applications (ICTA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.8799999952316284,"id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320337504","display_name":"Research and Development","ror":"https://ror.org/027s68j25"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":4,"referenced_works":["https://openalex.org/W4226443758","https://openalex.org/W4294891535","https://openalex.org/W4308259483","https://openalex.org/W4396505671"],"related_works":["https://openalex.org/W3126544799","https://openalex.org/W3104333581","https://openalex.org/W2542565870","https://openalex.org/W3111828357","https://openalex.org/W3018398156","https://openalex.org/W2920832517","https://openalex.org/W4388827557","https://openalex.org/W4387877594","https://openalex.org/W2800613970","https://openalex.org/W2065031478"],"abstract_inverted_index":{"Spiking":[0,55],"Neural":[1,14],"Networks":[2,15],"(SNNs)":[3],"exhibit":[4],"superior":[5],"energy":[6,40,89,147,163],"efficiency":[7,41],"and":[8,42,64,146,154,162,170],"fault":[9,43,66,95],"tolerance":[10],"compared":[11],"to":[12,18,102],"Artificial":[13],"(ANNs).":[16],"Due":[17],"their":[19],"spike-based":[20],"nature,":[21],"input":[22],"signals":[23],"must":[24],"be":[25],"encoded":[26],"into":[27],"spike":[28],"trains.":[29],"However,":[30],"traditional":[31],"spiking":[32],"coding":[33,53],"schemes":[34],"often":[35],"encounter":[36],"a":[37,51,85,120,126,138],"trade-off":[38],"between":[39],"tolerance.":[44,67],"To":[45],"overcome":[46],"this":[47],"limitation,":[48],"we":[49,136],"propose":[50],"novel":[52],"scheme,":[54],"Sparse":[56],"Coding":[57],"(SSC),":[58],"which":[59],"achieves":[60],"both":[61],"high":[62],"sparsity":[63],"enhanced":[65],"SSC":[68,92],"not":[69],"only":[70],"improves":[71],"network":[72,94,112],"performance":[73],"but":[74],"also":[75],"reduces":[76],"the":[77,111,114,133,159],"number":[78],"of":[79,100,122,129,141],"spikes":[80],"by":[81],"93.69%,":[82],"resulting":[83],"in":[84,88],"76.47%":[86],"increase":[87],"efficiency.":[90],"Additionally,":[91],"enhances":[93],"tolerance,":[96],"with":[97,125],"accuracy":[98,140],"improvements":[99],"up":[101],"12.06%":[103],"under":[104],"identical":[105],"noise":[106],"interference":[107],"conditions.":[108],"We":[109],"deployed":[110],"on":[113],"ZCU102":[115],"FPGA":[116],"platform,":[117],"operating":[118],"at":[119],"frequency":[121],"200":[123],"MHz":[124],"power":[127],"consumption":[128,148,164],"409":[130],"mW.":[131],"On":[132],"MNIST":[134],"dataset,":[135],"achieved":[137],"classification":[139],"95.84%.":[142],"The":[143],"training":[144],"speed":[145,161],"were":[149,165],"12656":[150],"frames":[151,167],"per":[152,157,168,173],"second":[153,169],"0.032":[155],"mJ":[156,172],"image,":[158],"inference":[160],"19279":[166],"0.021":[171],"image.":[174]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
