{"id":"https://openalex.org/W2167482232","doi":"https://doi.org/10.1145/2744769.2744779","title":"A low power unsupervised spike sorting accelerator insensitive to clustering initialization in sub-optimal feature space","display_name":"A low power unsupervised spike sorting accelerator insensitive to clustering initialization in sub-optimal feature space","publication_year":2015,"publication_date":"2015-06-02","ids":{"openalex":"https://openalex.org/W2167482232","doi":"https://doi.org/10.1145/2744769.2744779","mag":"2167482232"},"language":"en","primary_location":{"id":"doi:10.1145/2744769.2744779","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2744769.2744779","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 52nd Annual Design Automation Conference","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/A5046317279","display_name":"Zhewei Jiang","orcid":"https://orcid.org/0000-0002-7893-9208"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Zhewei Jiang","raw_affiliation_strings":["Columbia University, New York, NY"],"affiliations":[{"raw_affiliation_string":"Columbia University, New York, NY","institution_ids":["https://openalex.org/I78577930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100341244","display_name":"Qi Wang","orcid":"https://orcid.org/0000-0002-1404-582X"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qi Wang","raw_affiliation_strings":["Columbia University, New York, NY"],"affiliations":[{"raw_affiliation_string":"Columbia University, New York, NY","institution_ids":["https://openalex.org/I78577930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5011887658","display_name":"Mingoo Seok","orcid":"https://orcid.org/0000-0002-9722-0979"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mingoo Seok","raw_affiliation_strings":["Columbia University, New York, NY"],"affiliations":[{"raw_affiliation_string":"Columbia University, New York, NY","institution_ids":["https://openalex.org/I78577930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5046317279"],"corresponding_institution_ids":["https://openalex.org/I78577930"],"apc_list":null,"apc_paid":null,"fwci":0.9864,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.79452637,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9998000264167786,"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"}},{"id":"https://openalex.org/T10581","display_name":"Neural dynamics and brain function","score":0.9997000098228455,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.8589825630187988},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7554657459259033},{"id":"https://openalex.org/keywords/spike-sorting","display_name":"Spike sorting","score":0.7420978546142578},{"id":"https://openalex.org/keywords/initialization","display_name":"Initialization","score":0.7190136313438416},{"id":"https://openalex.org/keywords/sorting","display_name":"Sorting","score":0.608461856842041},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.5553582310676575},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5255181789398193},{"id":"https://openalex.org/keywords/spike","display_name":"Spike (software development)","score":0.5065473318099976},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4938557744026184},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4881666302680969},{"id":"https://openalex.org/keywords/throughput","display_name":"Throughput","score":0.41138172149658203},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2073463499546051}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.8589825630187988},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7554657459259033},{"id":"https://openalex.org/C2777613131","wikidata":"https://www.wikidata.org/wiki/Q2003571","display_name":"Spike sorting","level":3,"score":0.7420978546142578},{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.7190136313438416},{"id":"https://openalex.org/C111696304","wikidata":"https://www.wikidata.org/wiki/Q2303697","display_name":"Sorting","level":2,"score":0.608461856842041},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.5553582310676575},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5255181789398193},{"id":"https://openalex.org/C2781390188","wikidata":"https://www.wikidata.org/wiki/Q25203449","display_name":"Spike (software development)","level":2,"score":0.5065473318099976},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4938557744026184},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4881666302680969},{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.41138172149658203},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2073463499546051},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"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/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.0},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2744769.2744779","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2744769.2744779","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 52nd Annual Design Automation Conference","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.4699999988079071,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1608291116","https://openalex.org/W1673310716","https://openalex.org/W1999118804","https://openalex.org/W2044719021","https://openalex.org/W2090224802","https://openalex.org/W2098179667","https://openalex.org/W2118459608","https://openalex.org/W2119235711","https://openalex.org/W2126751256","https://openalex.org/W2135871626","https://openalex.org/W2136104104","https://openalex.org/W2139778447","https://openalex.org/W2160039585","https://openalex.org/W2160405996","https://openalex.org/W2160997918","https://openalex.org/W2170936641","https://openalex.org/W3168433459","https://openalex.org/W6685077929"],"related_works":["https://openalex.org/W3136143059","https://openalex.org/W3178771700","https://openalex.org/W1968361507","https://openalex.org/W2037099207","https://openalex.org/W3035015922","https://openalex.org/W4399305221","https://openalex.org/W2124872530","https://openalex.org/W2097405940","https://openalex.org/W2366422659","https://openalex.org/W4377004198"],"abstract_inverted_index":{"Online":[0],"unsupervised":[1,46],"spike":[2],"sorting":[3],"or":[4],"clustering":[5,16,81,93,98],"is":[6,82],"an":[7,43,73],"integral":[8],"component":[9],"of":[10,27,62,114,142,149],"implantable":[11],"closed-loop":[12],"brain-computer-interface":[13],"systems.":[14],"Robust":[15],"performance":[17],"against":[18],"various":[19],"non-idealities":[20],"such":[21],"as":[22],"poor":[23,97],"initialization":[24],"and":[25,36,45,80,84,105,111,123,130],"order-of-arrival":[26],"inputs":[28],"are":[29,117,128],"desirable":[30],"while":[31,137],"meeting":[32],"the":[33,60,71,101,108,112,115,134,139,146],"minimal":[34],"area":[35,113],"power":[37,106,109],"requirements":[38],"for":[39,65],"implants.":[40],"We":[41],"explore":[42],"online":[44],"spike-sorting":[47],"algorithm":[48],"utilizing":[49],"a":[50,87],"low-overhead":[51],"feature":[52,57,78],"screening":[53,79],"process":[54],"that":[55,76],"improves":[56],"discriminability":[58],"in":[59,86],"use":[61],"sub-optimal":[63],"features":[64],"reducing":[66],"hardware":[67],"complexity.":[68],"Based":[69],"on":[70],"algorithm,":[72],"accelerator":[74,116],"architecture":[75],"performs":[77],"devised":[83],"implemented":[85],"65-nm":[88],"high-VTH":[89],"CMOS,":[90],"largely":[91],"improving":[92],"accuracy":[94],"even":[95],"with":[96],"initialization.":[99],"In":[100],"post-layout":[102],"static":[103],"timing":[104],"simulation,":[107],"consumption":[110],"found":[118],"to":[119],"be":[120],"2.17":[121],"\u03bcW/ch":[122],"0.052":[124],"\u03bcm2/ch,":[125],"respectively,":[126],"which":[127],"53%":[129],"25%":[131],"smaller":[132],"than":[133],"previous":[135],"designs,":[136],"achieving":[138],"required":[140],"throughput":[141],"420":[143],"sorting/s":[144],"at":[145],"supply":[147],"voltage":[148],"300mV.":[150]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}