{"id":"https://openalex.org/W2588868474","doi":"https://doi.org/10.1109/allerton.2016.7852244","title":"On Compressive orthonormal Sensing","display_name":"On Compressive orthonormal Sensing","publication_year":2016,"publication_date":"2016-09-01","ids":{"openalex":"https://openalex.org/W2588868474","doi":"https://doi.org/10.1109/allerton.2016.7852244","mag":"2588868474"},"language":"en","primary_location":{"id":"doi:10.1109/allerton.2016.7852244","is_oa":false,"landing_page_url":"https://doi.org/10.1109/allerton.2016.7852244","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 54th Annual Allerton Conference on Communication, Control, and Computing (Allerton)","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/A5101704070","display_name":"Yi Zhou","orcid":"https://orcid.org/0000-0002-3982-9145"},"institutions":[{"id":"https://openalex.org/I70983195","display_name":"Syracuse University","ror":"https://ror.org/025r5qe02","country_code":"US","type":"education","lineage":["https://openalex.org/I70983195"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yi Zhou","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, Syracuse University, Syracuse, NY, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, Syracuse University, Syracuse, NY, USA","institution_ids":["https://openalex.org/I70983195"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066928490","display_name":"Huishuai Zhang","orcid":"https://orcid.org/0000-0003-2711-7295"},"institutions":[{"id":"https://openalex.org/I70983195","display_name":"Syracuse University","ror":"https://ror.org/025r5qe02","country_code":"US","type":"education","lineage":["https://openalex.org/I70983195"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Huishuai Zhang","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, Syracuse University, Syracuse, NY, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, Syracuse University, Syracuse, NY, USA","institution_ids":["https://openalex.org/I70983195"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100384384","display_name":"Yingbin Liang","orcid":"https://orcid.org/0000-0003-2631-4262"},"institutions":[{"id":"https://openalex.org/I70983195","display_name":"Syracuse University","ror":"https://ror.org/025r5qe02","country_code":"US","type":"education","lineage":["https://openalex.org/I70983195"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yingbin Liang","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, Syracuse University, Syracuse, NY, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, Syracuse University, Syracuse, NY, USA","institution_ids":["https://openalex.org/I70983195"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101704070"],"corresponding_institution_ids":["https://openalex.org/I70983195"],"apc_list":null,"apc_paid":null,"fwci":0.9119,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.75598806,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"299","last_page":"305"},"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/T11739","display_name":"Microwave Imaging and Scattering Analysis","score":0.9975000023841858,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"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/T10727","display_name":"Ultrasound Imaging and Elastography","score":0.9955000281333923,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/orthonormal-basis","display_name":"Orthonormal basis","score":0.9741988182067871},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.6943532824516296},{"id":"https://openalex.org/keywords/coherence","display_name":"Coherence (philosophical gambling strategy)","score":0.6571154594421387},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6238026022911072},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.5706748366355896},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4917490780353546},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.41761380434036255},{"id":"https://openalex.org/keywords/coherent-sampling","display_name":"Coherent sampling","score":0.41337287425994873},{"id":"https://openalex.org/keywords/logarithm","display_name":"Logarithm","score":0.41000333428382874},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.33103570342063904},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3067847788333893},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.10799536108970642},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.09453034400939941},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.07265236973762512},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.07230013608932495}],"concepts":[{"id":"https://openalex.org/C5806529","wikidata":"https://www.wikidata.org/wiki/Q2365325","display_name":"Orthonormal basis","level":2,"score":0.9741988182067871},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.6943532824516296},{"id":"https://openalex.org/C2781181686","wikidata":"https://www.wikidata.org/wiki/Q4226068","display_name":"Coherence (philosophical gambling strategy)","level":2,"score":0.6571154594421387},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6238026022911072},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.5706748366355896},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4917490780353546},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.41761380434036255},{"id":"https://openalex.org/C31942786","wikidata":"https://www.wikidata.org/wiki/Q679800","display_name":"Coherent sampling","level":4,"score":0.41337287425994873},{"id":"https://openalex.org/C39927690","wikidata":"https://www.wikidata.org/wiki/Q11197","display_name":"Logarithm","level":2,"score":0.41000333428382874},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.33103570342063904},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3067847788333893},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.10799536108970642},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.09453034400939941},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.07265236973762512},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.07230013608932495},{"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/allerton.2016.7852244","is_oa":false,"landing_page_url":"https://doi.org/10.1109/allerton.2016.7852244","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 54th Annual Allerton Conference on Communication, Control, and Computing (Allerton)","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":44,"referenced_works":["https://openalex.org/W1604604340","https://openalex.org/W1608074891","https://openalex.org/W1653728640","https://openalex.org/W1787402657","https://openalex.org/W1800346269","https://openalex.org/W1969271729","https://openalex.org/W1999352252","https://openalex.org/W2029816571","https://openalex.org/W2066211830","https://openalex.org/W2077925928","https://openalex.org/W2087326866","https://openalex.org/W2107882641","https://openalex.org/W2109357213","https://openalex.org/W2121835854","https://openalex.org/W2129638195","https://openalex.org/W2129812935","https://openalex.org/W2137198385","https://openalex.org/W2145096794","https://openalex.org/W2164452299","https://openalex.org/W2166163936","https://openalex.org/W2167836216","https://openalex.org/W2168399082","https://openalex.org/W2191788215","https://openalex.org/W2296616510","https://openalex.org/W2407170444","https://openalex.org/W2480981092","https://openalex.org/W2541214910","https://openalex.org/W2556237558","https://openalex.org/W2588868474","https://openalex.org/W2950958145","https://openalex.org/W2964340701","https://openalex.org/W3104501706","https://openalex.org/W4244670803","https://openalex.org/W4250955649","https://openalex.org/W6636014196","https://openalex.org/W6636600324","https://openalex.org/W6636904114","https://openalex.org/W6638242754","https://openalex.org/W6638425411","https://openalex.org/W6650267568","https://openalex.org/W6657892929","https://openalex.org/W6687193754","https://openalex.org/W6714122766","https://openalex.org/W6721875038"],"related_works":["https://openalex.org/W2370850565","https://openalex.org/W2381894435","https://openalex.org/W2158224665","https://openalex.org/W2296214397","https://openalex.org/W2029951831","https://openalex.org/W2072372040","https://openalex.org/W3141309046","https://openalex.org/W2105877514","https://openalex.org/W2071548530","https://openalex.org/W2379468505"],"abstract_inverted_index":{"The":[0],"Compressive":[1],"Sensing":[2],"(CS)":[3],"approach":[4],"for":[5,45,118,135,149,166],"recovering":[6],"sparse":[7],"signal":[8,94,114],"with":[9,65,168],"orthonormal":[10,47,66,122,136,154,169],"measurements":[11,67],"has":[12],"been":[13],"studied":[14],"under":[15,120],"various":[16],"notions":[17,22],"of":[18,23,31,54,56,63,84,92,153,178],"coherence.":[19,98],"However,":[20],"existing":[21,132,187],"coherence":[24],"either":[25],"do":[26],"not":[27],"exploit":[28],"the":[29,32,61,89,93,96,111,159,163],"structure":[30,91],"underlying":[33,112],"signal,":[34],"or":[35],"are":[36],"too":[37],"complicated":[38],"to":[39,110,128,145,192],"provide":[40],"an":[41],"explicit":[42],"sampling":[43,62,105,133,164,180,188],"scheme":[44,106,125],"all":[46,121],"basis":[48],"sets.":[49],"Consequently,":[50],"there":[51],"is":[52,108,116],"lack":[53],"understanding":[55],"key":[57],"factors":[58],"that":[59,86,107],"guide":[60],"CS":[64,119,167],"and":[68,95,115,138,182],"achieve":[69],"as":[70,74],"low":[71],"sample":[72,142],"complexity":[73,143],"possible.":[75],"In":[76],"this":[77],"paper,":[78],"we":[79,102,157],"introduce":[80],"a":[81,104,129,140,174],"new":[82],"notion":[83],"\u03c0-coherence":[85],"exploits":[87],"both":[88],"sparsity":[90],"local":[97],"Based":[99],"on":[100,162],"\u03c0-coherence,":[101],"propose":[103,173],"adapted":[109],"true":[113],"applicable":[117],"basis.":[123,155],"Our":[124],"outperforms":[126],"(up":[127,144],"constant":[130],"factor)":[131],"schemes":[134,165,189],"measurements,":[137],"achieves":[139],"near-optimal":[141],"certain":[146],"logarithm":[147],"factors)":[148],"several":[150],"popular":[151],"choices":[152],"Furthermore,":[156],"characterize":[158],"necessary":[160],"conditions":[161],"measurements.":[170],"We":[171],"then":[172],"practical":[175],"multi-phase":[176],"implementation":[177],"our":[179],"scheme,":[181],"verify":[183],"its":[184],"advantage":[185],"over":[186],"via":[190],"application":[191],"magnetic":[193],"resonance":[194],"imaging":[195],"(MRI)":[196],"in":[197],"medical":[198],"science.":[199]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
