{"id":"https://openalex.org/W2594833489","doi":"https://doi.org/10.1109/acssc.2016.7869594","title":"Principal subspace estimation for low-rank Toeplitz covariance matrices with binary sensing","display_name":"Principal subspace estimation for low-rank Toeplitz covariance matrices with binary sensing","publication_year":2016,"publication_date":"2016-11-01","ids":{"openalex":"https://openalex.org/W2594833489","doi":"https://doi.org/10.1109/acssc.2016.7869594","mag":"2594833489"},"language":"en","primary_location":{"id":"doi:10.1109/acssc.2016.7869594","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acssc.2016.7869594","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 50th Asilomar Conference on Signals, Systems and Computers","raw_type":"proceedings-article"},"type":"conference-paper","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/A5013839479","display_name":"Haoyu Fu","orcid":"https://orcid.org/0000-0002-2108-7729"},"institutions":[{"id":"https://openalex.org/I52357470","display_name":"The Ohio State University","ror":"https://ror.org/00rs6vg23","country_code":"US","type":"education","lineage":["https://openalex.org/I52357470"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Haoyu Fu","raw_affiliation_strings":["Department of Electrical and Computer Engineering, The Ohio State University, Columbus, Ohio"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, The Ohio State University, Columbus, Ohio","institution_ids":["https://openalex.org/I52357470"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053809095","display_name":"Yuejie Chi","orcid":"https://orcid.org/0000-0002-6766-5459"},"institutions":[{"id":"https://openalex.org/I52357470","display_name":"The Ohio State University","ror":"https://ror.org/00rs6vg23","country_code":"US","type":"education","lineage":["https://openalex.org/I52357470"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yuejie Chi","raw_affiliation_strings":["Department of Electrical and Computer Engineering, The Ohio State University, Columbus, Ohio"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, The Ohio State University, Columbus, Ohio","institution_ids":["https://openalex.org/I52357470"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I52357470"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1344","last_page":"1348"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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/T10931","display_name":"Direction-of-Arrival Estimation Techniques","score":0.9997000098228455,"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/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9994000196456909,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/toeplitz-matrix","display_name":"Toeplitz matrix","score":0.7839266061782837},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.6168851256370544},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.5820755958557129},{"id":"https://openalex.org/keywords/covariance-matrix","display_name":"Covariance matrix","score":0.5645127892494202},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.49450060725212097},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4589340388774872},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.442608505487442},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.41711103916168213},{"id":"https://openalex.org/keywords/decorrelation","display_name":"Decorrelation","score":0.41183996200561523},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.35368409752845764},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.20214831829071045},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.15780073404312134}],"concepts":[{"id":"https://openalex.org/C147710293","wikidata":"https://www.wikidata.org/wiki/Q849428","display_name":"Toeplitz matrix","level":2,"score":0.7839266061782837},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6168851256370544},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.5820755958557129},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.5645127892494202},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.49450060725212097},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4589340388774872},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.442608505487442},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.41711103916168213},{"id":"https://openalex.org/C177860922","wikidata":"https://www.wikidata.org/wiki/Q788608","display_name":"Decorrelation","level":2,"score":0.41183996200561523},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.35368409752845764},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.20214831829071045},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.15780073404312134},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/acssc.2016.7869594","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acssc.2016.7869594","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 50th Asilomar Conference on Signals, Systems and Computers","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":21,"referenced_works":["https://openalex.org/W1541064563","https://openalex.org/W1608096849","https://openalex.org/W2060430274","https://openalex.org/W2081540728","https://openalex.org/W2107411554","https://openalex.org/W2112038498","https://openalex.org/W2116950495","https://openalex.org/W2118550318","https://openalex.org/W2128131274","https://openalex.org/W2133105246","https://openalex.org/W2137198385","https://openalex.org/W2963381277","https://openalex.org/W2963879045","https://openalex.org/W2964003909","https://openalex.org/W2964200481","https://openalex.org/W2969605534","https://openalex.org/W3098045837","https://openalex.org/W4388534025","https://openalex.org/W6636113716","https://openalex.org/W6677837081","https://openalex.org/W6767058080"],"related_works":["https://openalex.org/W1604939135","https://openalex.org/W2127058578","https://openalex.org/W2098040275","https://openalex.org/W2353873167","https://openalex.org/W2170667396","https://openalex.org/W2002899408","https://openalex.org/W4310218166","https://openalex.org/W2886934452","https://openalex.org/W1489099099","https://openalex.org/W2024369332"],"abstract_inverted_index":{"In":[0,37],"this":[1],"paper,":[2],"we":[3],"consider":[4,163],"the":[5,9,22,30,39,84,88,108,111,115,124,133,140,164],"problem":[6],"of":[7,12,87,96,110,123,146],"estimating":[8],"principal":[10],"subspace":[11,112],"data":[13,40,89],"in":[14,55,66,114,139,154],"decentralized":[15],"sensing":[16],"systems":[17],"with":[18],"resource":[19],"constraints,":[20],"where":[21],"sensors":[23],"only":[24],"transmit":[25],"a":[26,46,120],"single":[27],"bit":[28],"to":[29,33,136],"fusion":[31],"center":[32],"minimize":[34],"communication":[35],"costs.":[36],"particular,":[38],"covariance":[41],"matrix":[42],"is":[43,71,144],"modeled":[44],"as":[45,58],"low-rank":[47,141],"Toeplitz":[48,165],"positive":[49],"semidefinite":[50],"(PSD)":[51],"matrix,":[52],"which":[53],"arises":[54],"applications":[56],"such":[57],"array":[59],"signal":[60],"processing":[61],"and":[62,143],"power":[63],"spectrum":[64],"estimation":[65],"cognitive":[67],"radios.":[68],"Our":[69],"algorithm":[70],"based":[72,81],"on":[73,82],"convex":[74],"regularization":[75],"using":[76],"carefully":[77],"designed":[78],"one-bit":[79],"measurements":[80,126],"comparing":[83],"energy":[85],"projections":[86],"seen":[90],"at":[91],"each":[92],"sensor":[93],"onto":[94],"pairs":[95],"randomly":[97,128],"selected":[98],"Gaussian":[99],"vectors.":[100],"We":[101],"provide":[102],"finite":[103],"sample":[104],"performance":[105],"guarantees":[106],"for":[107],"accuracy":[109],"estimate":[113],"rank-one":[116],"case,":[117,142],"even":[118],"when":[119],"constant":[121],"fraction":[122],"1-bit":[125],"are":[127],"flipped.":[129],"Numerical":[130],"experiments":[131],"demonstrate":[132],"method":[134],"continues":[135],"work":[137],"well":[138],"capable":[145],"separating":[147],"close":[148],"located":[149],"modes":[150],"from":[151],"fewer":[152],"bits":[153],"direction-of-arrival":[155],"estimation,":[156],"outperforming":[157],"existing":[158],"approaches":[159],"that":[160],"do":[161],"not":[162],"structure.":[166]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}