{"id":"https://openalex.org/W2990440057","doi":"https://doi.org/10.1109/access.2021.3076186","title":"Determinant-Based Fast Greedy Sensor Selection Algorithm","display_name":"Determinant-Based Fast Greedy Sensor Selection Algorithm","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W2990440057","doi":"https://doi.org/10.1109/access.2021.3076186","mag":"2990440057"},"language":"en","primary_location":{"id":"doi:10.1109/access.2021.3076186","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3076186","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09417233.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09417233.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5079583545","display_name":"Yuji Saito","orcid":"https://orcid.org/0000-0003-2804-8076"},"institutions":[{"id":"https://openalex.org/I201537933","display_name":"Tohoku University","ror":"https://ror.org/01dq60k83","country_code":"JP","type":"education","lineage":["https://openalex.org/I201537933"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Yuji Saito","raw_affiliation_strings":["Tohoku University, Sendai, Japan"],"raw_orcid":"https://orcid.org/0000-0003-2804-8076","affiliations":[{"raw_affiliation_string":"Tohoku University, Sendai, Japan","institution_ids":["https://openalex.org/I201537933"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027646710","display_name":"Taku Nonomura","orcid":"https://orcid.org/0000-0001-7739-7104"},"institutions":[{"id":"https://openalex.org/I201537933","display_name":"Tohoku University","ror":"https://ror.org/01dq60k83","country_code":"JP","type":"education","lineage":["https://openalex.org/I201537933"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Taku Nonomura","raw_affiliation_strings":["Tohoku University, Sendai, Japan"],"raw_orcid":"https://orcid.org/0000-0001-7739-7104","affiliations":[{"raw_affiliation_string":"Tohoku University, Sendai, Japan","institution_ids":["https://openalex.org/I201537933"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054423300","display_name":"Keigo Yamada","orcid":"https://orcid.org/0000-0001-8399-9574"},"institutions":[{"id":"https://openalex.org/I201537933","display_name":"Tohoku University","ror":"https://ror.org/01dq60k83","country_code":"JP","type":"education","lineage":["https://openalex.org/I201537933"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Keigo Yamada","raw_affiliation_strings":["Tohoku University, Sendai, Japan"],"raw_orcid":"https://orcid.org/0000-0001-8399-9574","affiliations":[{"raw_affiliation_string":"Tohoku University, Sendai, Japan","institution_ids":["https://openalex.org/I201537933"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086238401","display_name":"Kumi Nakai","orcid":"https://orcid.org/0000-0002-8618-6381"},"institutions":[{"id":"https://openalex.org/I201537933","display_name":"Tohoku University","ror":"https://ror.org/01dq60k83","country_code":"JP","type":"education","lineage":["https://openalex.org/I201537933"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kumi Nakai","raw_affiliation_strings":["Tohoku University, Sendai, Japan"],"raw_orcid":"https://orcid.org/0000-0002-8618-6381","affiliations":[{"raw_affiliation_string":"Tohoku University, Sendai, Japan","institution_ids":["https://openalex.org/I201537933"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059308761","display_name":"Takayuki Nagata","orcid":"https://orcid.org/0000-0003-3644-4888"},"institutions":[{"id":"https://openalex.org/I201537933","display_name":"Tohoku University","ror":"https://ror.org/01dq60k83","country_code":"JP","type":"education","lineage":["https://openalex.org/I201537933"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takayuki Nagata","raw_affiliation_strings":["Tohoku University, Sendai, Japan"],"raw_orcid":"https://orcid.org/0000-0003-3644-4888","affiliations":[{"raw_affiliation_string":"Tohoku University, Sendai, Japan","institution_ids":["https://openalex.org/I201537933"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006557728","display_name":"Keisuke Asai","orcid":"https://orcid.org/0000-0002-9330-4972"},"institutions":[{"id":"https://openalex.org/I201537933","display_name":"Tohoku University","ror":"https://ror.org/01dq60k83","country_code":"JP","type":"education","lineage":["https://openalex.org/I201537933"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Keisuke Asai","raw_affiliation_strings":["Tohoku University, Sendai, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tohoku University, Sendai, Japan","institution_ids":["https://openalex.org/I201537933"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012602916","display_name":"Yasuo Sasaki","orcid":"https://orcid.org/0000-0003-0450-2764"},"institutions":[{"id":"https://openalex.org/I60134161","display_name":"Nagoya University","ror":"https://ror.org/04chrp450","country_code":"JP","type":"education","lineage":["https://openalex.org/I60134161"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yasuo Sasaki","raw_affiliation_strings":["Nagoya University, Nagoya, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nagoya University, Nagoya, Japan","institution_ids":["https://openalex.org/I60134161"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077522032","display_name":"Daisuke Tsubakino","orcid":"https://orcid.org/0000-0002-7713-6833"},"institutions":[{"id":"https://openalex.org/I60134161","display_name":"Nagoya University","ror":"https://ror.org/04chrp450","country_code":"JP","type":"education","lineage":["https://openalex.org/I60134161"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Daisuke Tsubakino","raw_affiliation_strings":["Nagoya University, Nagoya, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nagoya University, Nagoya, Japan","institution_ids":["https://openalex.org/I60134161"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5079583545"],"corresponding_institution_ids":["https://openalex.org/I201537933"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":11.3987,"has_fulltext":true,"cited_by_count":80,"citation_normalized_percentile":{"value":0.99426497,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"9","issue":null,"first_page":"68535","last_page":"68551"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T11236","display_name":"Control Systems and Identification","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/algorithm","display_name":"Algorithm","score":0.6514518857002258},{"id":"https://openalex.org/keywords/oversampling","display_name":"Oversampling","score":0.5704267024993896},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5410747528076172},{"id":"https://openalex.org/keywords/greedy-algorithm","display_name":"Greedy algorithm","score":0.5168848037719727},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.47060948610305786},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.46012991666793823},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.4531259536743164},{"id":"https://openalex.org/keywords/undersampling","display_name":"Undersampling","score":0.4287908673286438},{"id":"https://openalex.org/keywords/maximization","display_name":"Maximization","score":0.4240614175796509},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.4104901850223541},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3719024062156677},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.15684327483177185}],"concepts":[{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6514518857002258},{"id":"https://openalex.org/C197323446","wikidata":"https://www.wikidata.org/wiki/Q331222","display_name":"Oversampling","level":3,"score":0.5704267024993896},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5410747528076172},{"id":"https://openalex.org/C51823790","wikidata":"https://www.wikidata.org/wiki/Q504353","display_name":"Greedy algorithm","level":2,"score":0.5168848037719727},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.47060948610305786},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.46012991666793823},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4531259536743164},{"id":"https://openalex.org/C136536468","wikidata":"https://www.wikidata.org/wiki/Q1225894","display_name":"Undersampling","level":2,"score":0.4287908673286438},{"id":"https://openalex.org/C2776330181","wikidata":"https://www.wikidata.org/wiki/Q18358244","display_name":"Maximization","level":2,"score":0.4240614175796509},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.4104901850223541},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3719024062156677},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.15684327483177185},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/access.2021.3076186","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3076186","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09417233.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1911.08757","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1911.08757","pdf_url":"https://arxiv.org/pdf/1911.08757","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:doaj.org/article:8366e8df17ec4804bf365f418c93d01a","is_oa":true,"landing_page_url":"https://doaj.org/article/8366e8df17ec4804bf365f418c93d01a","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 9, Pp 68535-68551 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2021.3076186","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3076186","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09417233.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G405651578","display_name":null,"funder_award_id":"JPMJAX20AD","funder_id":"https://openalex.org/F4320338246","funder_display_name":"ACT-X"},{"id":"https://openalex.org/G4543225726","display_name":null,"funder_award_id":"JPMJCR1763","funder_id":"https://openalex.org/F4320338075","funder_display_name":"Core Research for Evolutional Science and Technology"},{"id":"https://openalex.org/G7396185175","display_name":"\u6d41\u4f53\u6700\u9069\u5236\u5fa1\u306b\u5411\u3051\u305f\u9ad8\u901f\u9ad8\u7cbe\u5ea6\u30c7\u30fc\u30bf\u540c\u5316\u624b\u6cd5\u306e\u78ba\u7acb","funder_award_id":"JPMJPR1678","funder_id":"https://openalex.org/F4320334789","funder_display_name":"Japan Science and Technology Agency"}],"funders":[{"id":"https://openalex.org/F4320334789","display_name":"Japan Science and Technology Agency","ror":"https://ror.org/00097mb19"},{"id":"https://openalex.org/F4320338075","display_name":"Core Research for Evolutional Science and Technology","ror":"https://ror.org/00097mb19"},{"id":"https://openalex.org/F4320338246","display_name":"ACT-X","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2990440057.pdf","grobid_xml":"https://content.openalex.org/works/W2990440057.grobid-xml"},"referenced_works_count":37,"referenced_works":["https://openalex.org/W1680189815","https://openalex.org/W2014356541","https://openalex.org/W2047591100","https://openalex.org/W2049753327","https://openalex.org/W2068991306","https://openalex.org/W2112823474","https://openalex.org/W2119233169","https://openalex.org/W2124500362","https://openalex.org/W2169207653","https://openalex.org/W2254437089","https://openalex.org/W2582771730","https://openalex.org/W2748760860","https://openalex.org/W2751142080","https://openalex.org/W2800035578","https://openalex.org/W2955762689","https://openalex.org/W2963448313","https://openalex.org/W2964017122","https://openalex.org/W2990440057","https://openalex.org/W2993521327","https://openalex.org/W2999728064","https://openalex.org/W3033136070","https://openalex.org/W3042140472","https://openalex.org/W3046450754","https://openalex.org/W3087694753","https://openalex.org/W3089316803","https://openalex.org/W3093094851","https://openalex.org/W3098287931","https://openalex.org/W3102937078","https://openalex.org/W3104009841","https://openalex.org/W3104037750","https://openalex.org/W3118655244","https://openalex.org/W4229706427","https://openalex.org/W4230098943","https://openalex.org/W4238160257","https://openalex.org/W4249713861","https://openalex.org/W4250589301","https://openalex.org/W6772493270"],"related_works":["https://openalex.org/W32988189","https://openalex.org/W4308469503","https://openalex.org/W2904737874","https://openalex.org/W80466363","https://openalex.org/W4389233021","https://openalex.org/W2399571531","https://openalex.org/W2947132063","https://openalex.org/W4390415670","https://openalex.org/W4288337828","https://openalex.org/W4287816717"],"abstract_inverted_index":{"In":[0],"this":[1,139],"paper,":[2],"the":[3,14,19,29,32,47,50,57,60,63,71,76,82,95,98,107,124,130,134,144,148,154,158,168,178,182,190,194,198,204,207,210,214,219,223,236,240,251,255],"sparse":[4,20],"sensor":[5,21,225,233,241],"placement":[6],"problem":[7,48,159],"for":[8,56,105],"least-squares":[9],"estimation":[10,183,199],"is":[11,24,40,66,86,111,127,141,163,201],"considered,":[12],"and":[13,129,213],"previous":[15],"novel":[16],"approach":[17],"of":[18,28,31,46,59,62,75,84,90,109,115,123,133,147,153,170,206],"selection":[22],"algorithm":[23,104,140,156,180,238],"extended.":[25],"The":[26,54,151,173],"maximization":[27,58],"determinant":[30,61],"matrix":[33,38,65],"which":[34,227,246],"appears":[35],"in":[36,49,193,243,254],"pseudo-inverse":[37],"operations":[39],"employed":[41],"as":[42,73,203],"an":[43],"objective":[44,135,149],"function":[45,136],"present":[51],"extended":[52],"approach.":[53],"procedure":[55],"corresponding":[64],"proved":[67],"to":[68,218],"be":[69],"mathematically":[70],"same":[72],"that":[74,89,114,177],"previously":[77],"proposed":[78,155,179,237],"QR":[79],"method":[80],"when":[81,106],"number":[83,108],"sensors":[85,110],"less":[87],"than":[88,113,230],"state":[91,116],"variables":[92,117],"(undersampling).":[93],"On":[94],"other":[96,171,252],"hand,":[97],"authors":[99],"have":[100],"developed":[101],"a":[102,120,259],"new":[103],"greater":[112],"(oversampling).":[118],"Then,":[119],"unified":[121],"formulation":[122],"two":[125],"algorithms":[126,253],"derived,":[128],"lower":[131],"bound":[132],"given":[137],"by":[138,165,185],"shown":[142],"using":[143,160],"monotone":[145],"submodularity":[146],"function.":[150],"effectiveness":[152],"on":[157,258],"real":[161],"datasets":[162],"demonstrated":[164],"comparing":[166],"with":[167,189,250],"results":[169,175],"algorithms.":[172],"numerical":[174],"show":[176],"improves":[181],"error":[184,200],"approximately":[186],"10%":[187],"compared":[188],"conventional":[191],"methods":[192],"oversampling":[195,256],"case,":[196],"where":[197],"defined":[202],"ratio":[205],"difference":[208],"between":[209],"reconstructed":[211],"data":[212,217],"full":[215,220],"observation":[216],"observation.":[221],"For":[222],"NOAA-SST":[224],"problem,":[226],"has":[228],"more":[229],"ten":[231],"thousand":[232],"candidate":[234],"points,":[235],"selects":[239],"positions":[242],"few":[244],"seconds,":[245],"required":[247],"several":[248],"hours":[249],"case":[257],"3.40":[260],"GHz":[261],"computer.":[262]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":12},{"year":2024,"cited_by_count":14},{"year":2023,"cited_by_count":18},{"year":2022,"cited_by_count":17},{"year":2021,"cited_by_count":14}],"updated_date":"2026-06-02T09:04:35.204637","created_date":"2025-10-10T00:00:00"}
