{"id":"https://openalex.org/W2747803690","doi":"https://doi.org/10.1109/tsp.2017.2742983","title":"A Sampling Framework for Solving Physics-Driven Inverse Source Problems","display_name":"A Sampling Framework for Solving Physics-Driven Inverse Source Problems","publication_year":2017,"publication_date":"2017-08-22","ids":{"openalex":"https://openalex.org/W2747803690","doi":"https://doi.org/10.1109/tsp.2017.2742983","mag":"2747803690"},"language":"en","primary_location":{"id":"doi:10.1109/tsp.2017.2742983","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tsp.2017.2742983","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Signal Processing","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1109/tsp.2017.2742983","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5090649157","display_name":"John Murray\u2013Bruce","orcid":"https://orcid.org/0000-0002-1416-4175"},"institutions":[{"id":"https://openalex.org/I111088046","display_name":"Boston University","ror":"https://ror.org/05qwgg493","country_code":"US","type":"education","lineage":["https://openalex.org/I111088046"]},{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB","US"],"is_corresponding":false,"raw_author_name":"John Murray-Bruce","raw_affiliation_strings":["Communications and Signal Processing Group, Imperial College London, London, U.K","Department of Electrical and Computer Engineering, Boston University, Boston, MA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Communications and Signal Processing Group, Imperial College London, London, U.K","institution_ids":["https://openalex.org/I47508984"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Boston University, Boston, MA, USA","institution_ids":["https://openalex.org/I111088046"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053203917","display_name":"Pier Luigi Dragotti","orcid":"https://orcid.org/0000-0002-6073-2807"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Pier Luigi Dragotti","raw_affiliation_strings":["Communications and Signal Processing Group, Department of Electrical and Electronic Engineering, Imperial College London, London, U.K"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Communications and Signal Processing Group, Department of Electrical and Electronic Engineering, Imperial College London, London, U.K","institution_ids":["https://openalex.org/I47508984"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.0822,"has_fulltext":false,"cited_by_count":24,"citation_normalized_percentile":{"value":0.86225431,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"65","issue":"24","first_page":"6365","last_page":"6380"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9939000010490417,"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"}},"topics":[{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9939000010490417,"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"}},{"id":"https://openalex.org/T11205","display_name":"Numerical methods in inverse problems","score":0.9876999855041504,"subfield":{"id":"https://openalex.org/subfields/2610","display_name":"Mathematical Physics"},"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/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9858999848365784,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/inverse-problem","display_name":"Inverse problem","score":0.6762942671775818},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.6260225772857666},{"id":"https://openalex.org/keywords/partial-differential-equation","display_name":"Partial differential equation","score":0.5744192600250244},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.5509452819824219},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.5108630061149597},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.50450599193573},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.4965537190437317},{"id":"https://openalex.org/keywords/inverse","display_name":"Inverse","score":0.4663611650466919},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4466269314289093},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4391356110572815},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4092157483100891},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.358387291431427},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3249843418598175},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.23061826825141907},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.12881329655647278}],"concepts":[{"id":"https://openalex.org/C135252773","wikidata":"https://www.wikidata.org/wiki/Q1567213","display_name":"Inverse problem","level":2,"score":0.6762942671775818},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.6260225772857666},{"id":"https://openalex.org/C93779851","wikidata":"https://www.wikidata.org/wiki/Q271977","display_name":"Partial differential equation","level":2,"score":0.5744192600250244},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.5509452819824219},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.5108630061149597},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.50450599193573},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.4965537190437317},{"id":"https://openalex.org/C207467116","wikidata":"https://www.wikidata.org/wiki/Q4385666","display_name":"Inverse","level":2,"score":0.4663611650466919},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4466269314289093},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4391356110572815},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4092157483100891},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.358387291431427},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3249843418598175},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.23061826825141907},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.12881329655647278},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","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/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","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},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tsp.2017.2742983","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tsp.2017.2742983","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Signal Processing","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1702.05019","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1702.05019","pdf_url":"https://arxiv.org/pdf/1702.05019","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":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:spiral.imperial.ac.uk:10044/1/50271","is_oa":true,"landing_page_url":"http://hdl.handle.net/10044/1/50271","pdf_url":null,"source":{"id":"https://openalex.org/S4306401396","display_name":"Spiral (Imperial College London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I47508984","host_organization_name":"Imperial College London","host_organization_lineage":["https://openalex.org/I47508984"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"6380","raw_type":"Journal Article"}],"best_oa_location":{"id":"doi:10.1109/tsp.2017.2742983","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tsp.2017.2742983","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Signal Processing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":67,"referenced_works":["https://openalex.org/W203831624","https://openalex.org/W658512522","https://openalex.org/W1519837037","https://openalex.org/W1539472441","https://openalex.org/W1547358136","https://openalex.org/W1575011268","https://openalex.org/W1921756296","https://openalex.org/W1968502532","https://openalex.org/W1980448497","https://openalex.org/W1980570027","https://openalex.org/W2002663556","https://openalex.org/W2004421506","https://openalex.org/W2013150886","https://openalex.org/W2021811999","https://openalex.org/W2027932797","https://openalex.org/W2038594555","https://openalex.org/W2043620285","https://openalex.org/W2064314582","https://openalex.org/W2065656021","https://openalex.org/W2069074182","https://openalex.org/W2076776015","https://openalex.org/W2096086749","https://openalex.org/W2099267803","https://openalex.org/W2100761732","https://openalex.org/W2102909445","https://openalex.org/W2105233799","https://openalex.org/W2114070512","https://openalex.org/W2117905067","https://openalex.org/W2118682956","https://openalex.org/W2120625852","https://openalex.org/W2122679915","https://openalex.org/W2123811769","https://openalex.org/W2126700042","https://openalex.org/W2127617367","https://openalex.org/W2127786259","https://openalex.org/W2129906637","https://openalex.org/W2130403046","https://openalex.org/W2137003028","https://openalex.org/W2137129839","https://openalex.org/W2142780243","https://openalex.org/W2145758026","https://openalex.org/W2147117072","https://openalex.org/W2151346922","https://openalex.org/W2162446088","https://openalex.org/W2162960573","https://openalex.org/W2163889321","https://openalex.org/W2164278908","https://openalex.org/W2166153231","https://openalex.org/W2166500461","https://openalex.org/W2212377804","https://openalex.org/W2222833901","https://openalex.org/W2260356585","https://openalex.org/W2292001768","https://openalex.org/W2326057307","https://openalex.org/W2561836265","https://openalex.org/W2593899291","https://openalex.org/W2642675874","https://openalex.org/W2730620053","https://openalex.org/W3143762821","https://openalex.org/W4240884267","https://openalex.org/W4292363360","https://openalex.org/W6608261555","https://openalex.org/W6632376587","https://openalex.org/W6689361306","https://openalex.org/W6739726603","https://openalex.org/W6740777818","https://openalex.org/W7061399666"],"related_works":["https://openalex.org/W4317939968","https://openalex.org/W2112284452","https://openalex.org/W4390144857","https://openalex.org/W3085798047","https://openalex.org/W4281647907","https://openalex.org/W2374269412","https://openalex.org/W371123309","https://openalex.org/W2638372604","https://openalex.org/W2331917905","https://openalex.org/W3155039083"],"abstract_inverted_index":{"Partial":[0],"differential":[1,58],"equations":[2],"are":[3,15,144],"central":[4],"to":[5,116,124,134,156,209],"describing":[6],"many":[7,11],"physical":[8,52],"phenomena.":[9],"In":[10],"applications,":[12],"these":[13],"phenomena":[14],"observed":[16],"through":[17],"a":[18,40,45,72,100,129,177],"sensor":[19,106,154,194],"network,":[20],"with":[21],"the":[22,64,105,109,113,135,148,157,164,168,173,181,199],"aim":[23],"of":[24,47,92,104,128,138,150,160,180],"inferring":[25],"their":[26,211],"underlying":[27,140],"properties.":[28],"Leveraging":[29],"from":[30,71],"certain":[31],"results":[32,208],"in":[33],"sampling":[34],"and":[35,203],"approximation":[36,179],"theory,":[37],"we":[38,61,86,189],"present":[39,205],"new":[41,187],"framework":[42],"for":[43,51,147,197],"solving":[44,198],"class":[46],"inverse":[48,200],"source":[49,201],"problems":[50],"fields":[53],"governed":[54],"by":[55,79,98],"linear":[56,101],"partial":[57],"equations.":[59],"Specifically,":[60],"demonstrate":[62],"that":[63,118],"unknown":[65],"field":[66],"sources":[67],"can":[68,95],"be":[69,96],"recovered":[70],"sequence":[73,91,149,159],"of,":[74],"so":[75],"called,":[76],"generalized":[77,93,161,169,182],"measurements":[78,94,162],"using":[80],"multidimensional":[81,120],"frequency":[82],"estimation":[83],"techniques.":[84],"Next":[85],"show":[87],"that-for":[88],"physics-driven":[89],"fields-this":[90],"estimated":[97],"computing":[99],"weighted":[102],"sum":[103],"measurements;":[107],"whereby":[108],"exact":[110,158],"weights":[111],"(of":[112],"sums)":[114],"correspond":[115],"those":[117],"reproduce":[119],"exponentials,":[121],"when":[122,163],"used":[123],"linearly":[125],"combine":[126],"translates":[127],"particular":[130],"prototype":[131],"function":[132,137,166],"related":[133],"Green's":[136,165],"our":[139],"field.":[141],"Explicit":[142],"formulas":[143],"then":[145,204],"derived":[146],"weights,":[151],"which":[152],"map":[153],"samples":[155],"satisfies":[167],"Strang-Fix":[170],"condition.":[171],"Otherwise,":[172],"same":[174],"mapping":[175],"yields":[176],"close":[178],"measurements.":[183],"Based":[184],"on":[185],"this":[186],"framework,":[188],"develop":[190],"practical,":[191],"noise":[192],"robust,":[193],"network":[195],"strategies":[196],"problem,":[202],"numerical":[206],"simulation":[207],"verify":[210],"performance.":[212]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":1}],"updated_date":"2026-07-03T08:13:44.112507","created_date":"2025-10-10T00:00:00"}