{"id":"https://openalex.org/W2129013461","doi":null,"title":"Inferring sparse representations of continuous signals with continuous orthogonal matching pursuit.","display_name":"Inferring sparse representations of continuous signals with continuous orthogonal matching pursuit.","publication_year":2014,"publication_date":"2014-01-01","ids":{"openalex":"https://openalex.org/W2129013461","mag":"2129013461","pmid":"https://pubmed.ncbi.nlm.nih.gov/25914512","pmcid":"https://www.ncbi.nlm.nih.gov/pmc/articles/4408936"},"language":"en","primary_location":{"id":"pmid:25914512","doi":null,"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/25914512","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Advances in neural information processing systems","raw_type":"Journal Article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/4408936","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5082411215","display_name":"Karin Knudson","orcid":"https://orcid.org/0000-0003-1312-6473","observed_orcids":["https://orcid.org/0000-0003-1312-6473"]},"institutions":[{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Karin C Knudson","raw_affiliation_strings":["Department of Mathematics, The University of Texas at Austin"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics, The University of Texas at Austin","institution_ids":["https://openalex.org/I86519309"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023677501","display_name":"Jacob L. Yates","orcid":"https://orcid.org/0000-0001-8322-5982","observed_orcids":["https://orcid.org/0000-0001-8322-5982"]},"institutions":[{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jacob L Yates","raw_affiliation_strings":["Department of Neuroscience, The University of Texas at Austin"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Neuroscience, The University of Texas at Austin","institution_ids":["https://openalex.org/I86519309"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003362529","display_name":"Alexander C. Huk","orcid":"https://orcid.org/0000-0003-1430-6935","observed_orcids":["https://orcid.org/0000-0003-1430-6935"]},"institutions":[{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alexander C Huk","raw_affiliation_strings":["Center for Perceptual Systems, Departments of Psychology & Neuroscience, The University of Texas at Austin"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Perceptual Systems, Departments of Psychology & Neuroscience, The University of Texas at Austin","institution_ids":["https://openalex.org/I86519309"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5111930113","display_name":"JonathanW Pillow","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I20089843","display_name":"Princeton University","ror":"https://ror.org/00hx57361","country_code":"US","type":"education","lineage":["https://openalex.org/I20089843"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"JonathanW Pillow","raw_affiliation_strings":["Princeton Neuroscience Institute and Department of Psychology, Princeton University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Princeton Neuroscience Institute and Department of Psychology, Princeton University","institution_ids":["https://openalex.org/I20089843"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.3579,"has_fulltext":false,"cited_by_count":25,"citation_normalized_percentile":{"value":0.81055994,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":98},"biblio":{"volume":"27","issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9984999895095825,"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"}},"topics":[{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9984999895095825,"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/T11210","display_name":"Mathematical Analysis and Transform Methods","score":0.0010000000474974513,"subfield":{"id":"https://openalex.org/subfields/2604","display_name":"Applied Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.0,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/sparse-representation","display_name":"sparse representation","score":0.8059999942779541},{"id":"https://openalex.org/keywords/greedy-algorithm","display_name":"greedy algorithm","score":0.5680000185966492},{"id":"https://openalex.org/keywords/time-shift-estimation","display_name":"time shift estimation","score":0.6790000200271606},{"id":"https://openalex.org/keywords/amplitude-estimation","display_name":"amplitude estimation","score":0.6779999732971191},{"id":"https://openalex.org/keywords/spike-trains","display_name":"spike trains","score":0.7070000171661377},{"id":"https://openalex.org/keywords/electrophysiological-recording","display_name":"electrophysiological recording","score":0.7940000295639038},{"id":"https://openalex.org/keywords/fourier-domain","display_name":"Fourier domain","score":0.42100000381469727},{"id":"https://openalex.org/keywords/continuous-time-signals","display_name":"continuous-time signals","score":0.3050000071525574}],"concepts":[{"id":"https://openalex.org/C156872377","wikidata":"https://www.wikidata.org/wiki/Q6786281","display_name":"Matching pursuit","level":3,"score":0.9325233697891235},{"id":"https://openalex.org/C197424946","wikidata":"https://www.wikidata.org/wiki/Q1165717","display_name":"Waveform","level":3,"score":0.6392571926116943},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6084922552108765},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5955605506896973},{"id":"https://openalex.org/C99217422","wikidata":"https://www.wikidata.org/wiki/Q4867576","display_name":"Basis pursuit","level":4,"score":0.5096969604492188},{"id":"https://openalex.org/C180205008","wikidata":"https://www.wikidata.org/wiki/Q159190","display_name":"Amplitude","level":2,"score":0.4355577826499939},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.434354692697525},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.42823129892349243},{"id":"https://openalex.org/C17137986","wikidata":"https://www.wikidata.org/wiki/Q215067","display_name":"Orthogonality","level":2,"score":0.4210865795612335},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.42100194096565247},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37356868386268616},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3301425576210022},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3185851573944092},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.15007087588310242},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.08421134948730469},{"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/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"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":6,"locations":[{"id":"pmid:25914512","doi":null,"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/25914512","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Advances in neural information processing systems","raw_type":"Journal Article"},{"id":"pmh:oai:europepmc.org:3370731","doi":null,"is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/4408936","pdf_url":null,"source":{"id":"https://openalex.org/S4306400806","display_name":"Europe PMC (PubMed Central)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1303153112","host_organization_name":"European Bioinformatics Institute","host_organization_lineage":["https://openalex.org/I1303153112"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":null,"raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:4408936","doi":null,"is_oa":true,"landing_page_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC4408936/","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"Adv Neural Inf Process Syst","raw_type":"Text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.709.4970","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.709.4970","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://motion.cps.utexas.edu/wp-content/uploads/2014/11/knudson-yates-huk-pillow-NIPS2014.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.714.4573","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.714.4573","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://pillowlab.princeton.edu/pubs/Knudson_COMP_NIPS14.pdf","raw_type":"text"},{"id":"mag:2129013461","doi":null,"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/25914512","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"PubMed","raw_type":null}],"best_oa_location":{"id":"pmh:oai:europepmc.org:3370731","doi":null,"is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/4408936","pdf_url":null,"source":{"id":"https://openalex.org/S4306400806","display_name":"Europe PMC (PubMed Central)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1303153112","host_organization_name":"European Bioinformatics Institute","host_organization_lineage":["https://openalex.org/I1303153112"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":null,"raw_type":"Text"},"sustainable_development_goals":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G3049921696","display_name":"Neural time-integration underlying higher cognitive function","funder_award_id":"R01EY017366","funder_id":"https://openalex.org/F4320337350","funder_display_name":"National Eye Institute"},{"id":"https://openalex.org/G626189503","display_name":"CRCNS Detailed multi-neuron coding of decisions in parietal cortex","funder_award_id":"R01MH099611","funder_id":"https://openalex.org/F4320337346","funder_display_name":"National Institute of Mental Health"}],"funders":[{"id":"https://openalex.org/F4320337346","display_name":"National Institute of Mental Health","ror":"https://ror.org/04xeg9z08"},{"id":"https://openalex.org/F4320337350","display_name":"National Eye Institute","ror":"https://ror.org/03wkg3b53"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W566443111","https://openalex.org/W1986931325","https://openalex.org/W1989775522","https://openalex.org/W2071004250","https://openalex.org/W2113642685","https://openalex.org/W2127271355","https://openalex.org/W2135046866","https://openalex.org/W2143148420","https://openalex.org/W2158537680","https://openalex.org/W2160979406","https://openalex.org/W2289917018","https://openalex.org/W2546124103"],"related_works":["https://openalex.org/W2410896677","https://openalex.org/W4411193890","https://openalex.org/W2736301122","https://openalex.org/W2073038598","https://openalex.org/W2143148420","https://openalex.org/W7095309314","https://openalex.org/W4391922573","https://openalex.org/W3005164523","https://openalex.org/W7096703688","https://openalex.org/W2071860689"],"abstract_inverted_index":{"Many":[0],"signals,":[1],"such":[2],"as":[3,14],"spike":[4],"trains":[5],"recorded":[6],"in":[7,87,115,175],"multi-channel":[8],"electrophysiological":[9],"recordings,":[10],"may":[11,37],"be":[12],"represented":[13],"the":[15,33,41,47,51,92,128,131,142,153],"sparse":[16],"sum":[17],"of":[18,23,30,46,77,127],"translated":[19,125],"and":[20,27,44,64,73,80,139,166,178],"scaled":[21],"copies":[22,126],"waveforms":[24,48,72],"whose":[25],"timing":[26],"amplitudes":[28,79],"are":[29],"interest.":[31],"From":[32],"aggregate":[34],"signal,":[35],"one":[36],"seek":[38],"to":[39,91,141,145],"estimate":[40,148],"identities,":[42,62],"amplitudes,":[43,63],"translations":[45,104],"that":[49,122],"compose":[50],"signal.":[52],"Here":[53],"we":[54,113,157],"present":[55],"a":[56,88,120,136],"fast":[57],"method":[58,67],"for":[59,102],"recovering":[60],"these":[61,85],"translations.":[65],"The":[66],"involves":[68],"greedily":[69],"selecting":[70,119],"component":[71],"then":[74],"refining":[75],"estimates":[76],"their":[78],"translations,":[81],"moving":[82,140],"iteratively":[83],"between":[84],"steps":[86],"process":[89],"analogous":[90],"well-known":[93],"Orthogonal":[94,160],"Matching":[95,161],"Pursuit":[96,109,162],"(OMP)":[97],"algorithm":[98],"[11].":[99],"Our":[100],"approach":[101],"modeling":[103],"borrows":[105],"from":[106],"Continuous":[107,159],"Basis":[108],"(CBP)":[110],"[4],":[111],"which":[112,156],"extend":[114],"several":[116],"ways:":[117],"by":[118],"subspace":[121],"optimally":[123],"captures":[124],"waveforms,":[129],"replacing":[130],"convex":[132],"optimization":[133],"problem":[134],"with":[135],"greedy":[137],"approach,":[138],"Fourier":[143],"domain":[144],"more":[146],"precisely":[147],"time":[149],"shifts.":[150],"We":[151],"test":[152],"resulting":[154],"method,":[155],"call":[158],"(COMP),":[163],"on":[164],"simulated":[165],"neural":[167],"data,":[168],"where":[169],"it":[170],"shows":[171],"gains":[172],"over":[173],"CBP":[174],"both":[176],"speed":[177],"accuracy.":[179]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":4},{"year":2015,"cited_by_count":1}],"updated_date":"2026-11-10T11:39:43.021295","created_date":"2016-06-24T00:00:00"}