{"id":"https://openalex.org/W2060823036","doi":"https://doi.org/10.1109/tit.2013.2285214","title":"Signal Estimation With Additive Error Metrics in Compressed Sensing","display_name":"Signal Estimation With Additive Error Metrics in Compressed Sensing","publication_year":2013,"publication_date":"2013-10-10","ids":{"openalex":"https://openalex.org/W2060823036","doi":"https://doi.org/10.1109/tit.2013.2285214","mag":"2060823036"},"language":"en","primary_location":{"id":"doi:10.1109/tit.2013.2285214","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tit.2013.2285214","pdf_url":null,"source":{"id":"https://openalex.org/S4502562","display_name":"IEEE Transactions on Information Theory","issn_l":"0018-9448","issn":["0018-9448","1557-9654"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Information Theory","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1207.1760","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5035567238","display_name":"Jin Tan","orcid":"https://orcid.org/0000-0001-6550-964X"},"institutions":[{"id":"https://openalex.org/I137902535","display_name":"North Carolina State University","ror":"https://ror.org/04tj63d06","country_code":"US","type":"education","lineage":["https://openalex.org/I137902535"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Jin Tan","raw_affiliation_strings":["Department of Electrical and Computer Engineering, North Carolina State University, Raleigh, NC, USA","Dept. of Electr. & Comput. Eng, North Carolina State Univ., Raleigh, NC, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, North Carolina State University, Raleigh, NC, USA","institution_ids":["https://openalex.org/I137902535"]},{"raw_affiliation_string":"Dept. of Electr. & Comput. Eng, North Carolina State Univ., Raleigh, NC, USA","institution_ids":["https://openalex.org/I137902535"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091704246","display_name":"Danielle Carmon","orcid":null},"institutions":[{"id":"https://openalex.org/I1309191912","display_name":"Research Triangle Park Foundation","ror":"https://ror.org/03eqttr49","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I1309191912"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Danielle Carmon","raw_affiliation_strings":["IBM, Department of Cloud Systems Software, Research Triangle Park, NC, USA","Dept. of Cloud Syst. Software, IBM, Research Triangle Park, NC, USA"],"affiliations":[{"raw_affiliation_string":"IBM, Department of Cloud Systems Software, Research Triangle Park, NC, USA","institution_ids":[]},{"raw_affiliation_string":"Dept. of Cloud Syst. Software, IBM, Research Triangle Park, NC, USA","institution_ids":["https://openalex.org/I1309191912"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037316256","display_name":"Dror Baron","orcid":"https://orcid.org/0000-0002-6371-8496"},"institutions":[{"id":"https://openalex.org/I137902535","display_name":"North Carolina State University","ror":"https://ror.org/04tj63d06","country_code":"US","type":"education","lineage":["https://openalex.org/I137902535"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dror Baron","raw_affiliation_strings":["Department of Electrical and Computer Engineering, North Carolina State University, Raleigh, NC, USA","Dept. of Electr. & Comput. Eng, North Carolina State Univ., Raleigh, NC, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, North Carolina State University, Raleigh, NC, USA","institution_ids":["https://openalex.org/I137902535"]},{"raw_affiliation_string":"Dept. of Electr. & Comput. Eng, North Carolina State Univ., Raleigh, NC, USA","institution_ids":["https://openalex.org/I137902535"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5035567238"],"corresponding_institution_ids":["https://openalex.org/I137902535"],"apc_list":null,"apc_paid":null,"fwci":5.6374,"has_fulltext":false,"cited_by_count":21,"citation_normalized_percentile":{"value":0.96157998,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"60","issue":"1","first_page":"150","last_page":"158"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":1.0,"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":1.0,"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/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9987000226974487,"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"}},{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9986000061035156,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.7537600994110107},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.6584700345993042},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.6385291218757629},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.5571223497390747},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.548532247543335},{"id":"https://openalex.org/keywords/matching-pursuit","display_name":"Matching pursuit","score":0.47717157006263733},{"id":"https://openalex.org/keywords/decoupling","display_name":"Decoupling (probability)","score":0.45205917954444885},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.42489221692085266},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4063228666782379},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3450402021408081},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.20490750670433044},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.1917646825313568}],"concepts":[{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.7537600994110107},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6584700345993042},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.6385291218757629},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.5571223497390747},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.548532247543335},{"id":"https://openalex.org/C156872377","wikidata":"https://www.wikidata.org/wiki/Q6786281","display_name":"Matching pursuit","level":3,"score":0.47717157006263733},{"id":"https://openalex.org/C205606062","wikidata":"https://www.wikidata.org/wiki/Q5249645","display_name":"Decoupling (probability)","level":2,"score":0.45205917954444885},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.42489221692085266},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4063228666782379},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3450402021408081},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.20490750670433044},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.1917646825313568},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C133731056","wikidata":"https://www.wikidata.org/wiki/Q4917288","display_name":"Control engineering","level":1,"score":0.0}],"mesh":[],"locations_count":6,"locations":[{"id":"doi:10.1109/tit.2013.2285214","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tit.2013.2285214","pdf_url":null,"source":{"id":"https://openalex.org/S4502562","display_name":"IEEE Transactions on Information Theory","issn_l":"0018-9448","issn":["0018-9448","1557-9654"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Information Theory","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1207.1760","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1207.1760","pdf_url":"https://arxiv.org/pdf/1207.1760","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:CiteSeerX.psu:10.1.1.394.4190","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.394.4190","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www4.ncsu.edu/~jtan/pdf/ArbMetric_finalSub.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.645.8915","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.645.8915","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://people.engr.ncsu.edu/dzbaron/pdf/ArbMetric2014TCB.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.704.3369","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.704.3369","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www4.ncsu.edu/%7Ejtan/pdf/TransIT2014.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.747.7576","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.747.7576","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://arxiv.org/pdf/1207.1760.pdf","raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1207.1760","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1207.1760","pdf_url":"https://arxiv.org/pdf/1207.1760","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"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.5600000023841858}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W1492251543","https://openalex.org/W1615740763","https://openalex.org/W1663973292","https://openalex.org/W1987485949","https://openalex.org/W2020390700","https://openalex.org/W2023584248","https://openalex.org/W2060823036","https://openalex.org/W2077621940","https://openalex.org/W2082029531","https://openalex.org/W2085493178","https://openalex.org/W2090842051","https://openalex.org/W2099111195","https://openalex.org/W2099448014","https://openalex.org/W2101435685","https://openalex.org/W2104266187","https://openalex.org/W2104357403","https://openalex.org/W2114908991","https://openalex.org/W2116394223","https://openalex.org/W2117577039","https://openalex.org/W2127271355","https://openalex.org/W2129638195","https://openalex.org/W2132660002","https://openalex.org/W2135859872","https://openalex.org/W2138358551","https://openalex.org/W2141556672","https://openalex.org/W2143236825","https://openalex.org/W2144015943","https://openalex.org/W2145096794","https://openalex.org/W2156178499","https://openalex.org/W2160051394","https://openalex.org/W2166670884","https://openalex.org/W2289917018","https://openalex.org/W2296616510","https://openalex.org/W2531349076","https://openalex.org/W2532988047","https://openalex.org/W2537629200","https://openalex.org/W2550925785","https://openalex.org/W3098848552","https://openalex.org/W3146003712","https://openalex.org/W4212863985","https://openalex.org/W4250955649","https://openalex.org/W4298266977","https://openalex.org/W6682749907"],"related_works":["https://openalex.org/W2098521117","https://openalex.org/W4319793311","https://openalex.org/W2465351041","https://openalex.org/W4385694579","https://openalex.org/W2340242818","https://openalex.org/W4300881421","https://openalex.org/W2103001330","https://openalex.org/W2262109992","https://openalex.org/W2241396314","https://openalex.org/W2436826437"],"abstract_inverted_index":{"Compressed":[0],"sensing":[1,59],"typically":[2],"deals":[3],"with":[4,61],"the":[5,17,24,32,67,70,87,92,98,128,145,175],"estimation":[6,33,105],"of":[7,19,26,31],"a":[8,56,82,103,123],"system":[9],"input":[10,27],"from":[11],"its":[12],"noise-corrupted":[13],"linear":[14],"measurements,":[15],"where":[16],"number":[18,25],"measurements":[20],"is":[21,35,102,117],"smaller":[22],"than":[23],"components.":[28],"The":[29,100],"performance":[30,131,147],"process":[34],"usually":[36],"quantified":[37],"by":[38,90,97],"some":[39],"standard":[40],"error":[41,46,64,94,136],"metric":[42,95],"such":[43,160],"as":[44,161],"squared":[45],"or":[47],"support":[48],"set":[49],"error.":[50],"In":[51],"this":[52],"correspondence,":[53],"we":[54,80,121],"consider":[55],"noisy":[57],"compressed":[58],"problem":[60],"any":[62,134],"additive":[63,93,135],"metric.":[65,137],"Under":[66],"assumption":[68],"that":[69,85,114,155],"relaxed":[71,162],"belief":[72,163],"propagation":[73,164],"method":[74,125],"matches":[75],"Tanaka's":[76],"fixed":[77],"point":[78],"equation,":[79],"propose":[81],"general":[83,124],"algorithm":[84,101,116,157],"estimates":[86],"original":[88],"signal":[89],"minimizing":[91],"defined":[96],"user.":[99],"pointwise":[104],"process,":[106],"and":[107,110,120,143,167,173],"thus":[108],"simple":[109],"fast.":[111],"We":[112,138],"verify":[113],"our":[115,156,180],"asymptotically":[118],"optimal,":[119],"describe":[122],"to":[126],"compute":[127],"fundamental":[129],"information-theoretic":[130],"limit":[132],"for":[133,149,179],"provide":[139],"several":[140],"example":[141,181],"metrics,":[142],"give":[144],"theoretical":[146,177],"limits":[148,178],"these":[150],"cases.":[151],"Experimental":[152],"results":[153],"show":[154],"outperforms":[158],"methods":[159],"(relaxed":[165],"BP)":[166],"compressive":[168],"sampling":[169],"matching":[170],"pursuit":[171],"(CoSaMP),":[172],"reaches":[174],"suggested":[176],"metrics.":[182]},"counts_by_year":[{"year":2020,"cited_by_count":3},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":4},{"year":2013,"cited_by_count":6}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}