{"id":"https://openalex.org/W2963653648","doi":"https://doi.org/10.1109/allerton.2012.6483468","title":"Coherence-based performance guarantees of Orthogonal Matching Pursuit","display_name":"Coherence-based performance guarantees of Orthogonal Matching Pursuit","publication_year":2012,"publication_date":"2012-10-01","ids":{"openalex":"https://openalex.org/W2963653648","doi":"https://doi.org/10.1109/allerton.2012.6483468","mag":"2963653648"},"language":"en","primary_location":{"id":"doi:10.1109/allerton.2012.6483468","doi":"https://doi.org/10.1109/allerton.2012.6483468","is_oa":false,"landing_page_url":"https://doi.org/10.1109/allerton.2012.6483468","pdf_url":null,"source":{"id":"https://openalex.org/S4306417658","display_name":"Allerton Conference on Communication, Control, and Computing","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 50th Annual Allerton Conference on Communication, Control, and Computing (Allerton)","raw_type":"proceedings-article"},"volume":null,"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/A5053809095","display_name":"Yuejie Chi","orcid":"https://orcid.org/0000-0002-6766-5459","observed_orcids":["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, Ohio State University, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Ohio State University, USA","institution_ids":["https://openalex.org/I52357470"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037795370","display_name":"Robert Calderbank","orcid":"https://orcid.org/0000-0003-2084-9717","observed_orcids":["https://orcid.org/0000-0003-2084-9717"]},"institutions":[{"id":"https://openalex.org/I170897317","display_name":"Duke University","ror":"https://ror.org/00py81415","country_code":"US","type":"education","lineage":["https://openalex.org/I170897317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Robert Calderbank","raw_affiliation_strings":["ZDepartment of Electrical and Computer Engineering, Duke University, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ZDepartment of Electrical and Computer Engineering, Duke University, USA","institution_ids":["https://openalex.org/I170897317"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.9633,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.87826087,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"2003","last_page":"2009"},"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/T11210","display_name":"Mathematical Analysis and Transform Methods","score":0.0,"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/T10136","display_name":"Statistical Methods and Inference","score":0.0,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/orthogonal-matching-pursuit","display_name":"orthogonal matching pursuit","score":0.984000027179718},{"id":"https://openalex.org/keywords/coherence","display_name":"coherence","score":0.5},{"id":"https://openalex.org/keywords/sparse-signal-recovery","display_name":"sparse signal recovery","score":0.7670000195503235},{"id":"https://openalex.org/keywords/support-recovery","display_name":"support recovery","score":0.9359999895095825},{"id":"https://openalex.org/keywords/measurement-matrix","display_name":"measurement matrix","score":0.46799999475479126},{"id":"https://openalex.org/keywords/stopping-criterion","display_name":"stopping rules","score":0.6769999861717224},{"id":"https://openalex.org/keywords/signal-to-noise-ratio","display_name":"signal-to-noise ratio","score":0.8140000104904175},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"compressed sensing","score":0.6190000176429749}],"concepts":[{"id":"https://openalex.org/C156872377","wikidata":"https://www.wikidata.org/wiki/Q6786281","display_name":"Matching pursuit","level":3,"score":0.9182629585266113},{"id":"https://openalex.org/C2781181686","wikidata":"https://www.wikidata.org/wiki/Q4226068","display_name":"Coherence (philosophical gambling strategy)","level":2,"score":0.7309632897377014},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6035928130149841},{"id":"https://openalex.org/C2983961125","wikidata":"https://www.wikidata.org/wiki/Q1288707","display_name":"Stopping rule","level":2,"score":0.5437873005867004},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.540311872959137},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5369111895561218},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.5210477709770203},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.4922691881656647},{"id":"https://openalex.org/C70958404","wikidata":"https://www.wikidata.org/wiki/Q7512728","display_name":"Signal reconstruction","level":4,"score":0.4786349833011627},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.47510942816734314},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.4569237232208252},{"id":"https://openalex.org/C13944312","wikidata":"https://www.wikidata.org/wiki/Q7512748","display_name":"Signal-to-noise ratio (imaging)","level":2,"score":0.41281816363334656},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.39462965726852417},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.383151650428772},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.36703938245773315},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3170100450515747},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.3013772964477539},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.21657812595367432},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1519213616847992},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.09267804026603699},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.06610193848609924},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/allerton.2012.6483468","doi":"https://doi.org/10.1109/allerton.2012.6483468","is_oa":false,"landing_page_url":"https://doi.org/10.1109/allerton.2012.6483468","pdf_url":null,"source":{"id":"https://openalex.org/S4306417658","display_name":"Allerton Conference on Communication, Control, and Computing","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 50th Annual Allerton Conference on Communication, Control, and Computing (Allerton)","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.762.5048","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.762.5048","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/1209.6267.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"sustainable_development_goals_aurora":[],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1492288302","https://openalex.org/W1683886983","https://openalex.org/W2020775053","https://openalex.org/W2037586880","https://openalex.org/W2078204800","https://openalex.org/W2083511239","https://openalex.org/W2098704159","https://openalex.org/W2115447612","https://openalex.org/W2116148865","https://openalex.org/W2129131372","https://openalex.org/W2134474909","https://openalex.org/W2138548210","https://openalex.org/W2140856955","https://openalex.org/W2163985430","https://openalex.org/W2296616510","https://openalex.org/W2964307271","https://openalex.org/W3101762025","https://openalex.org/W3104197796","https://openalex.org/W4250955649","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W2725593879","https://openalex.org/W2493602032","https://openalex.org/W2962740860","https://openalex.org/W2790607945","https://openalex.org/W2013768136","https://openalex.org/W337141585","https://openalex.org/W2074602575","https://openalex.org/W1971870985","https://openalex.org/W3087777689","https://openalex.org/W2949638768"],"abstract_inverted_index":{"In":[0,30,79],"this":[1],"paper,":[2],"we":[3],"present":[4],"coherence-based":[5],"performance":[6,82,122,133],"guarantees":[7,83,123,134],"of":[8,20,34,90,98,116],"Orthogonal":[9],"Matching":[10],"Pursuit":[11],"(OMP)":[12],"for":[13,124,135],"both":[14],"support":[15,126],"recovery":[16],"and":[17,140],"signal":[18,75,107],"reconstruction":[19],"sparse":[21],"signals":[22],"when":[23],"the":[24,53,59,81,87,91,95,99,105,113,117,141],"measurements":[25],"are":[26,46,129],"corrupted":[27],"by":[28],"noise.":[29],"particular,":[31,80],"two":[32],"variants":[33],"OMP":[35,70,136],"either":[36],"with":[37,42,64,76,131],"known":[38],"sparsity":[39],"level":[40],"or":[41],"a":[43,73],"stopping":[44],"rule":[45],"analyzed.":[47],"It":[48],"is":[49],"shown":[50],"that":[51],"if":[52],"measurement":[54,92],"matrix":[55,93],"X":[56],"\u03f5":[57],"Cn\u00d7psatisfies":[58],"strong":[60],"coherence":[61],"property,":[62],"then":[63],"n":[65],"\u2273":[66],"O(k":[67],"log":[68],"p),":[69],"will":[71],"recover":[72],"k-sparse":[74],"high":[77],"probability.":[78],"obtained":[84],"here":[85],"separate":[86],"properties":[88,96],"required":[89,97],"from":[94],"signal,":[100],"which":[101],"depends":[102],"critically":[103],"on":[104],"minimum":[106],"to":[108],"noise":[109],"ratio":[110],"rather":[111],"than":[112],"power":[114],"profiles":[115],"signal.":[118],"We":[119],"also":[120],"provide":[121],"partial":[125],"recovery.":[127],"Comparisons":[128],"given":[130],"other":[132],"using":[137],"worst-case":[138],"analysis":[139],"sorted":[142],"one":[143],"step":[144],"thresholding":[145],"algorithm.":[146]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":2},{"year":2013,"cited_by_count":1}],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2019-07-30T00:00:00"}
