{"id":"https://openalex.org/W3202411835","doi":"https://doi.org/10.1109/tsp.2021.3114977","title":"A Two Stage Generalized Block Orthogonal Matching Pursuit (TSGBOMP) Algorithm","display_name":"A Two Stage Generalized Block Orthogonal Matching Pursuit (TSGBOMP) Algorithm","publication_year":2020,"publication_date":"2020-08-18","ids":{"openalex":"https://openalex.org/W3202411835","doi":"https://doi.org/10.1109/tsp.2021.3114977","mag":"3202411835"},"language":null,"primary_location":{"id":"pmh:oai:arXiv.org:2008.08031","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2008.08031","pdf_url":"https://arxiv.org/pdf/2008.08031","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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"},"type":"preprint","indexed_in":["arxiv"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2008.08031","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5006331313","display_name":"Samrat Mukhopadhyay","orcid":"https://orcid.org/0000-0002-6389-5185"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mukhopadhyay, Samrat","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5072872028","display_name":"Mrityunjoy Chakraborty","orcid":"https://orcid.org/0000-0003-4009-9554"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chakraborty, Mrityunjoy","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9987000226974487,"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/T10057","display_name":"Face and Expression Recognition","score":0.9969000220298767,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/matching-pursuit","display_name":"Matching pursuit","score":0.763238251209259},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5792611837387085},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4986851215362549},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.47610458731651306},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.43294209241867065},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.40502557158470154},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3427105247974396},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.20384538173675537},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.13018161058425903}],"concepts":[{"id":"https://openalex.org/C156872377","wikidata":"https://www.wikidata.org/wiki/Q6786281","display_name":"Matching pursuit","level":3,"score":0.763238251209259},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5792611837387085},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4986851215362549},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.47610458731651306},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.43294209241867065},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.40502557158470154},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3427105247974396},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.20384538173675537},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.13018161058425903},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"pmh:oai:arXiv.org:2008.08031","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2008.08031","pdf_url":"https://arxiv.org/pdf/2008.08031","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2008.08031","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2008.08031","pdf_url":"https://arxiv.org/pdf/2008.08031","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W143004564","https://openalex.org/W1977520307","https://openalex.org/W1988529089","https://openalex.org/W2033419225","https://openalex.org/W2071282831","https://openalex.org/W2111730426","https://openalex.org/W2114129195","https://openalex.org/W2125680629","https://openalex.org/W2127271355","https://openalex.org/W2129131372","https://openalex.org/W2135780853","https://openalex.org/W2140856955","https://openalex.org/W2141433180","https://openalex.org/W2147276092","https://openalex.org/W2160979406","https://openalex.org/W2170792849","https://openalex.org/W2296616510","https://openalex.org/W2734811486","https://openalex.org/W2947569882","https://openalex.org/W2963219644","https://openalex.org/W2964333607","https://openalex.org/W3079238949","https://openalex.org/W3125735862","https://openalex.org/W4250955649"],"related_works":["https://openalex.org/W2042644197","https://openalex.org/W2073241848","https://openalex.org/W2785927776","https://openalex.org/W2020549994","https://openalex.org/W4220674950","https://openalex.org/W3127070406","https://openalex.org/W1545552580","https://openalex.org/W2883468993","https://openalex.org/W3099222149","https://openalex.org/W2099811626"],"abstract_inverted_index":{"Recovery":[0],"of":[1,9,16,43,90,106,121,193,211],"an":[2],"unknown":[3],"sparse":[4,28,31,35,126],"signal":[5,127],"from":[6],"a":[7,67,76,91,172],"few":[8],"its":[10],"projections":[11],"is":[12,75,110,157,200],"the":[13,41,72,83,95,99,107,116,122,134,140,155,176,179,197,212],"key":[14],"objective":[15],"compressed":[17],"sensing.":[18],"Often":[19],"one":[20],"comes":[21],"across":[22],"signals":[23],"that":[24,154,178,189,196],"are":[25,30,183,191],"not":[26,54],"ordinarily":[27],"but":[29],"blockwise.":[32],"Existing":[33],"block":[34,45,49,78,119,125],"recovery":[36,181],"algorithms":[37],"like":[38],"BOMP":[39],"make":[40],"assumption":[42],"uniform":[44],"size":[46],"and":[47,65,128,159],"known":[48],"boundaries,":[50],"which":[51],"are,":[52],"however,":[53],"very":[55],"practical":[56],"in":[57,98],"many":[58],"applications.":[59],"This":[60],"paper":[61],"addresses":[62],"this":[63],"problem":[64],"proposes":[66],"two":[68],"step":[69],"procedure,":[70],"where":[71,150],"first":[73,100,114],"stage":[74,81,85],"coarse":[77],"location":[79],"identification":[80],"while":[82],"second":[84],"carries":[86],"out":[87,112,153],"finer":[88],"localization":[89],"non-zero":[92],"cluster":[93],"within":[94],"window":[96],"selected":[97],"stage.":[101],"A":[102],"detailed":[103],"convergence":[104],"analysis":[105,141],"proposed":[108,213],"algorithm":[109,214],"carried":[111],"by":[113],"defining":[115],"so-called":[117],"pseudoblock-interleaved":[118],"RIP":[120],"given":[123],"generalized":[124],"then":[129],"imposing":[130],"upper":[131],"bounds":[132,182],"on":[133,175],"corresponding":[135],"RIC.":[136],"We":[137],"also":[138],"extend":[139],"for":[142],"complex":[143],"vector":[144],"as":[145,147,215],"well":[146],"matrix":[148,168],"entries":[149],"it":[151],"turns":[152],"extension":[156],"non-trivial":[158],"requires":[160],"special":[161],"care.":[162],"Furthermore,":[163],"assuming":[164],"real":[165],"Gaussian":[166],"sensing":[167],"entries,":[169],"we":[170],"find":[171],"lower":[173,186],"bound":[174,187,199],"probability":[177],"derived":[180,198],"satisfied.":[184],"The":[185],"suggests":[188],"there":[190],"sets":[192],"parameters":[194],"such":[195],"satisfied":[201],"with":[202],"high":[203],"probability.":[204],"Simulation":[205],"results":[206],"confirm":[207],"significantly":[208],"improved":[209],"performance":[210],"compared":[216],"to":[217],"BOMP.":[218]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3}],"updated_date":"2026-08-11T07:18:39.950985","created_date":"2021-10-11T00:00:00"}