{"id":"https://openalex.org/W4321484021","doi":"https://doi.org/10.1109/tsp.2023.3247138","title":"On the Foundation of Sparsity Constrained Sensing\u2014 Part I: Sampling Theory and Robust Remainder Problem","display_name":"On the Foundation of Sparsity Constrained Sensing\u2014 Part I: Sampling Theory and Robust Remainder Problem","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4321484021","doi":"https://doi.org/10.1109/tsp.2023.3247138"},"language":"en","primary_location":{"id":"doi:10.1109/tsp.2023.3247138","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2023.3247138","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"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 Signal Processing","raw_type":"journal-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/A5101702107","display_name":"Hanshen Xiao","orcid":"https://orcid.org/0000-0003-3380-4518"},"institutions":[{"id":"https://openalex.org/I126820664","display_name":"Vassar College","ror":"https://ror.org/022x6qg61","country_code":"US","type":"education","lineage":["https://openalex.org/I126820664"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hanshen Xiao","raw_affiliation_strings":["CSAIL and the EECS Department, MIT, Cambridge, MA, USA"],"raw_orcid":"https://orcid.org/0000-0003-3380-4518","affiliations":[{"raw_affiliation_string":"CSAIL and the EECS Department, MIT, Cambridge, MA, USA","institution_ids":["https://openalex.org/I126820664"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100677021","display_name":"Yaowen Zhang","orcid":"https://orcid.org/0009-0003-5727-6462"},"institutions":[{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yaowen Zhang","raw_affiliation_strings":["College of Computer and Information Science, Southwest University, Chongqing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer and Information Science, Southwest University, Chongqing, China","institution_ids":["https://openalex.org/I142108993"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021178964","display_name":"Beining Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Beining Zhou","raw_affiliation_strings":["Department of Computer Science, Stanford University, Stanford, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Stanford University, Stanford, CA, USA","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047341940","display_name":"Guoqiang Xiao","orcid":"https://orcid.org/0000-0003-2165-476X"},"institutions":[{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guoqiang Xiao","raw_affiliation_strings":["College of Computer and Information Science, Southwest University, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0003-2165-476X","affiliations":[{"raw_affiliation_string":"College of Computer and Information Science, Southwest University, Chongqing, China","institution_ids":["https://openalex.org/I142108993"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":2645,"currency":"USD","value_usd":2645},"apc_paid":null,"fwci":1.6348,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.79330473,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"71","issue":null,"first_page":"1263","last_page":"1276"},"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/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9991999864578247,"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"}},{"id":"https://openalex.org/T10931","display_name":"Direction-of-Arrival Estimation Techniques","score":0.9991999864578247,"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":0.7074830532073975},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.6518709659576416},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6148489117622375},{"id":"https://openalex.org/keywords/remainder","display_name":"Remainder","score":0.5296112298965454},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.49503058195114136},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.47947296500205994},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.44581204652786255},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.4289048910140991},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.37410715222358704},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2605535387992859},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.10545739531517029},{"id":"https://openalex.org/keywords/arithmetic","display_name":"Arithmetic","score":0.08984124660491943},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.07529553771018982}],"concepts":[{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.7074830532073975},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.6518709659576416},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6148489117622375},{"id":"https://openalex.org/C39613435","wikidata":"https://www.wikidata.org/wiki/Q846677","display_name":"Remainder","level":2,"score":0.5296112298965454},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.49503058195114136},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.47947296500205994},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.44581204652786255},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.4289048910140991},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.37410715222358704},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2605535387992859},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.10545739531517029},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.08984124660491943},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.07529553771018982},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"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/tsp.2023.3247138","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2023.3247138","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"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 Signal Processing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W1494887041","https://openalex.org/W1976826674","https://openalex.org/W1996692478","https://openalex.org/W2029816571","https://openalex.org/W2035657841","https://openalex.org/W2042465044","https://openalex.org/W2059422068","https://openalex.org/W2093541223","https://openalex.org/W2098174516","https://openalex.org/W2099186079","https://openalex.org/W2101675075","https://openalex.org/W2107906890","https://openalex.org/W2107982002","https://openalex.org/W2119667497","https://openalex.org/W2122838565","https://openalex.org/W2126153569","https://openalex.org/W2129131372","https://openalex.org/W2144909930","https://openalex.org/W2145096794","https://openalex.org/W2149551443","https://openalex.org/W2152185946","https://openalex.org/W2164390589","https://openalex.org/W2164452299","https://openalex.org/W2267105192","https://openalex.org/W2528243277","https://openalex.org/W2611232330","https://openalex.org/W2767831780","https://openalex.org/W2785173750","https://openalex.org/W2807984534","https://openalex.org/W2962852363","https://openalex.org/W2962910706","https://openalex.org/W2963668942","https://openalex.org/W3003337346","https://openalex.org/W3088022619","https://openalex.org/W3104214777","https://openalex.org/W3106031576","https://openalex.org/W4229991983","https://openalex.org/W4250431399","https://openalex.org/W4250955649","https://openalex.org/W4321607984"],"related_works":["https://openalex.org/W4315487898","https://openalex.org/W2088904828","https://openalex.org/W617989196","https://openalex.org/W2032199336","https://openalex.org/W2904183727","https://openalex.org/W2347282152","https://openalex.org/W2039575089","https://openalex.org/W4385351587","https://openalex.org/W2140321063","https://openalex.org/W4367182748"],"abstract_inverted_index":{"In":[0],"the":[1,5,13,31,52,80,84,137,143,166,180,195,201,208,216,221,224,230,240,245,262,268],"first":[2],"part":[3],"of":[4,22,55,73,86,108,113,128,142,169,223,267],"series":[6],"papers,":[7],"we":[8,147,176,219],"set":[9],"out":[10],"to":[11,58,78,95,120,155,164],"answer":[12],"following":[14],"fundamental":[15],"question:":[16],"for":[17],"constrained":[18,42,68],"sampling,":[19,183],"what":[20],"kind":[21],"signal":[23,57],"can":[24,152],"be":[25,153],"uniquely":[26],"represented":[27],"or":[28,64,102,258],"recovered":[29],"by":[30],"(distributed)":[32],"discrete":[33],"sample":[34,60],"sequence(s)":[35],"obtained?":[36],"We":[37,66,123,250],"term":[38],"this":[39],"study":[40],"assparsity":[41],"sensingorsparse":[43],"sensing.":[44],"It":[45],"is":[46,93,162,248,272],"different":[47],"fromcompressed":[48],"sensing,":[49,210],"which":[50,75,105,184,228],"exploits":[51],"sparse":[53],"representation":[54,168],"a":[56,71,99,170,173,212,275],"reduce":[59],"complexity":[61],"(compressed":[62],"sampling":[63,87,97,144,233,269],"acquisition).":[65],"usesparsity":[67],"sensingto":[69],"denote":[70],"class":[72],"methods":[74],"are":[76],"devoted":[77],"improving":[79],"efficiency":[81],"and":[82,118,126,135,139,178,207,244],"reducing":[83],"cost":[85],"implementation":[88],"itself.":[89],"The":[90],"\u201csparsity\u201d":[91],"here":[92],"referred":[94],"as":[96,112,132],"at":[98],"low":[100],"temporal":[101],"spatial":[103],"rate,":[104],"captures":[106],"applications":[107],"cheaper":[109],"hardware":[110],"such":[111],"lower":[114],"power,":[115],"less":[116],"memory":[117],"throughput":[119],"implement":[121],"sampling.":[122],"take":[124],"frequency":[125],"direction":[127],"arrival":[129],"(DoA)":[130],"estimation":[131,199,254],"concrete":[133],"examples":[134],"give":[136],"necessary":[138],"sufficient":[140],"conditions":[141],"strategy.":[145],"Interestingly,":[146],"prove":[148,251],"that":[149],"these":[150],"problems":[151],"reduced":[154],"some":[156],"(multiple)":[157],"remainder":[158,226],"model,":[159],"where":[160],"it":[161],"equivalent":[163],"studying":[165],"residue":[167],"signal.":[171],"As":[172],"straightforward":[174],"corollary,":[175],"supplement":[177],"complete":[179],"theory":[181],"ofco-prime":[182],"receives":[185],"considerable":[186],"attention":[187],"over":[188],"last":[189],"decade.":[190],"Our":[191],"results":[192],"also":[193],"connect":[194],"two":[196],"classic":[197],"parameter":[198,241],"frameworks,":[200],"Chinese":[202],"Remainder":[203],"Theorem":[204],"(CRT)":[205],"method":[206],"co-prime":[209],"with":[211,234],"unified":[213],"interpretation.":[214],"On":[215],"other":[217],"aspect,":[218],"advance":[220],"understanding":[222],"robust":[225],"problem,":[227],"models":[229],"case":[231],"when":[232],"noise.":[235],"A":[236],"sharpened":[237],"tradeoff":[238],"between":[239],"dynamic":[242],"range":[243],"error":[246,277],"bound":[247,279],"derived.":[249],"that,":[252],"for$N$-frequency":[253],"in":[255],"either":[256],"complex":[257],"real":[259],"waveforms,":[260],"once":[261],"least":[263],"common":[264],"multiple":[265],"(lcm)":[266],"rates":[270],"selected":[271],"sufficiently":[273],"large,":[274],"constant":[276],"tolerance":[278],"independent":[280],"of$N$is":[281],"approached.":[282]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2025-10-10T00:00:00"}