{"id":"https://openalex.org/W2735396979","doi":"https://doi.org/10.23919/acc.2017.7963161","title":"Blind subspace system identification with Riemannian optimization","display_name":"Blind subspace system identification with Riemannian optimization","publication_year":2017,"publication_date":"2017-05-01","ids":{"openalex":"https://openalex.org/W2735396979","doi":"https://doi.org/10.23919/acc.2017.7963161","mag":"2735396979"},"language":"en","primary_location":{"id":"doi:10.23919/acc.2017.7963161","is_oa":false,"landing_page_url":"https://doi.org/10.23919/acc.2017.7963161","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 American Control Conference (ACC)","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/A5022966275","display_name":"Cassiano O. Becker","orcid":"https://orcid.org/0000-0003-4280-7411"},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Cassiano O. Becker","raw_affiliation_strings":["Department of Electrical and Systems Engineering, University of Pennsylvania, AE Philadelphia, PA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Systems Engineering, University of Pennsylvania, AE Philadelphia, PA, USA","institution_ids":["https://openalex.org/I79576946"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057261458","display_name":"V\u00edctor M. Preciado","orcid":"https://orcid.org/0000-0001-9998-8730"},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Victor M. Preciado","raw_affiliation_strings":["Department of Electrical and Systems Engineering, University of Pennsylvania, AE Philadelphia, PA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Systems Engineering, University of Pennsylvania, AE Philadelphia, PA, USA","institution_ids":["https://openalex.org/I79576946"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5022966275"],"corresponding_institution_ids":["https://openalex.org/I79576946"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.09005313,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1474","last_page":"1480"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9994000196456909,"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":0.9994000196456909,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9966999888420105,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9919000267982483,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.7264585494995117},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.6403398513793945},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.5929513573646545},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.539499044418335},{"id":"https://openalex.org/keywords/optimization-problem","display_name":"Optimization problem","score":0.5292676687240601},{"id":"https://openalex.org/keywords/relaxation","display_name":"Relaxation (psychology)","score":0.522114634513855},{"id":"https://openalex.org/keywords/system-identification","display_name":"System identification","score":0.47765815258026123},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.47398486733436584},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.46685248613357544},{"id":"https://openalex.org/keywords/parameter-identification-problem","display_name":"Parameter identification problem","score":0.46113359928131104},{"id":"https://openalex.org/keywords/matrix-completion","display_name":"Matrix completion","score":0.42423728108406067},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.375021368265152},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.33825749158859253},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.10422873497009277},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.09814965724945068},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.09428229928016663},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.08581456542015076}],"concepts":[{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.7264585494995117},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.6403398513793945},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5929513573646545},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.539499044418335},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.5292676687240601},{"id":"https://openalex.org/C2776029896","wikidata":"https://www.wikidata.org/wiki/Q3935810","display_name":"Relaxation (psychology)","level":2,"score":0.522114634513855},{"id":"https://openalex.org/C119247159","wikidata":"https://www.wikidata.org/wiki/Q1366192","display_name":"System identification","level":3,"score":0.47765815258026123},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.47398486733436584},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.46685248613357544},{"id":"https://openalex.org/C79610928","wikidata":"https://www.wikidata.org/wiki/Q1656743","display_name":"Parameter identification problem","level":3,"score":0.46113359928131104},{"id":"https://openalex.org/C2778459887","wikidata":"https://www.wikidata.org/wiki/Q6787865","display_name":"Matrix completion","level":3,"score":0.42423728108406067},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.375021368265152},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33825749158859253},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.10422873497009277},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.09814965724945068},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.09428229928016663},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.08581456542015076},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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/C2983447341","wikidata":"https://www.wikidata.org/wiki/Q1413083","display_name":"Model parameter","level":2,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","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/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"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/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/acc.2017.7963161","is_oa":false,"landing_page_url":"https://doi.org/10.23919/acc.2017.7963161","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 American Control Conference (ACC)","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":22,"referenced_works":["https://openalex.org/W120660877","https://openalex.org/W191817552","https://openalex.org/W1535144613","https://openalex.org/W1803592988","https://openalex.org/W2042182457","https://openalex.org/W2045512849","https://openalex.org/W2058078260","https://openalex.org/W2110355775","https://openalex.org/W2110662303","https://openalex.org/W2115723730","https://openalex.org/W2118550318","https://openalex.org/W2121202969","https://openalex.org/W2121667911","https://openalex.org/W2140867429","https://openalex.org/W2167623372","https://openalex.org/W2290276813","https://openalex.org/W2615836285","https://openalex.org/W4205293427","https://openalex.org/W4242433770","https://openalex.org/W6607748011","https://openalex.org/W6678342423","https://openalex.org/W6684641359"],"related_works":["https://openalex.org/W2320156573","https://openalex.org/W1480508098","https://openalex.org/W4286891655","https://openalex.org/W2141538351","https://openalex.org/W3209823386","https://openalex.org/W4292532243","https://openalex.org/W2053946710","https://openalex.org/W1997118413","https://openalex.org/W1604447007","https://openalex.org/W1576040274"],"abstract_inverted_index":{"Subspace":[0],"identification":[1,41,69,85,155,197],"methods":[2,8],"provide":[3],"a":[4,66,120,150,199],"reliable":[5],"set":[6],"of":[7,13,21,92,122,126,141,156,190,208],"to":[9,37,48,63,110,132,174],"recover":[10],"system":[11,51,84,102,157],"parameters":[12],"linear":[14],"dynamical":[15],"systems":[16],"based":[17,71],"on":[18,65,72],"the":[19,28,38,40,54,58,90,101,106,114,123,142,153,178,205],"observation":[20],"their":[22],"inputs":[23,59,159],"and":[24,45,103,158,193],"outputs.":[25],"However,":[26],"in":[27,177],"common":[29],"case":[30],"where":[31,113],"one":[32,140],"does":[33],"not":[34],"have":[35],"access":[36],"inputs,":[39],"problem":[42,91,203],"becomes":[43],"harder,":[44],"is":[46,117],"referred":[47],"as":[49,89,119,136,198],"blind":[50,82,195],"identification.":[52],"On":[53],"other":[55],"hand,":[56],"if":[57],"can":[60,76],"be":[61,77,133,175],"assumed":[62],"lie":[64],"known":[67],"subspace,":[68],"techniques":[70],"low-rank":[73,96,171,200],"matrix":[74,172,201],"recovery":[75],"applied.":[78],"In":[79,145],"this":[80,111,146,191],"case,":[81],"subspace":[83],"has":[86,129],"been":[87,130],"formulated":[88],"simultaneously":[93],"recovering":[94],"structured":[95],"matrices":[97],"associated":[98],"with":[99],"both":[100],"inputs.":[104],"Notwithstanding,":[105],"convex":[107],"relaxation":[108],"approach":[109,187],"problem,":[112],"objective":[115,143],"function":[116],"defined":[118],"sum":[121],"nuclear":[124],"norms":[125],"two":[127],"matrices,":[128],"shown":[131],"significantly":[134],"sub-optimal":[135],"it":[137],"typically":[138],"favors":[139],"terms.":[144],"work,":[147],"we":[148],"propose":[149],"method":[151],"for":[152],"joint":[154],"using":[160],"optimization":[161,166],"over":[162,204],"Riemann":[163],"manifolds.":[164],"Riemannian":[165],"defines":[167],"operators":[168],"that":[169],"allow":[170],"constraints":[173],"incorporated":[176],"search":[179],"space,":[180],"producing":[181],"feasible":[182],"solutions":[183],"by":[184],"construction.":[185],"Our":[186],"takes":[188],"advantage":[189],"capability":[192],"formulates":[194],"subsystem":[196],"approximation":[202],"product":[206],"manifold":[207],"fixed-rank":[209],"matrices.":[210]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}