{"id":"https://openalex.org/W2046186019","doi":"https://doi.org/10.1109/acssc.2014.7094749","title":"A fast proximal gradient algorithm for reconstructing nonnegative signals with sparse transform coefficients","display_name":"A fast proximal gradient algorithm for reconstructing nonnegative signals with sparse transform coefficients","publication_year":2014,"publication_date":"2014-11-01","ids":{"openalex":"https://openalex.org/W2046186019","doi":"https://doi.org/10.1109/acssc.2014.7094749","mag":"2046186019"},"language":"en","primary_location":{"id":"doi:10.1109/acssc.2014.7094749","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acssc.2014.7094749","pdf_url":null,"source":{"id":"https://openalex.org/S4363608593","display_name":"2014 48th Asilomar Conference on Signals, Systems and Computers","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"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":"2014 48th Asilomar Conference on Signals, Systems and Computers","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/A5106183477","display_name":"Renliang Gu","orcid":null},"institutions":[{"id":"https://openalex.org/I173911158","display_name":"Iowa State University","ror":"https://ror.org/04rswrd78","country_code":"US","type":"education","lineage":["https://openalex.org/I173911158"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Renliang Gu","raw_affiliation_strings":["ECpE Department, Iowa State University, Ames, IA","ECpE Department, Iowa State University, 3119 Coover Hall, Ames, IA 50011"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ECpE Department, Iowa State University, Ames, IA","institution_ids":["https://openalex.org/I173911158"]},{"raw_affiliation_string":"ECpE Department, Iowa State University, 3119 Coover Hall, Ames, IA 50011","institution_ids":["https://openalex.org/I173911158"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020320518","display_name":"A. Dogandzic","orcid":"https://orcid.org/0000-0002-3005-3686"},"institutions":[{"id":"https://openalex.org/I173911158","display_name":"Iowa State University","ror":"https://ror.org/04rswrd78","country_code":"US","type":"education","lineage":["https://openalex.org/I173911158"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Aleksandar Dogandzic","raw_affiliation_strings":["ECpE Department, Iowa State University, Ames, IA","ECpE Department, Iowa State University, 3119 Coover Hall, Ames, IA 50011"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ECpE Department, Iowa State University, Ames, IA","institution_ids":["https://openalex.org/I173911158"]},{"raw_affiliation_string":"ECpE Department, Iowa State University, 3119 Coover Hall, Ames, IA 50011","institution_ids":["https://openalex.org/I173911158"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.6121,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.80658874,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"1","issue":null,"first_page":"1662","last_page":"1667"},"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/T12015","display_name":"Photoacoustic and Ultrasonic Imaging","score":0.9990000128746033,"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/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.9987999796867371,"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/underdetermined-system","display_name":"Underdetermined system","score":0.6633778810501099},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.6201549172401428},{"id":"https://openalex.org/keywords/signal-reconstruction","display_name":"Signal reconstruction","score":0.6094040870666504},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.6046527028083801},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.599183976650238},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.5222386121749878},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.5208562016487122},{"id":"https://openalex.org/keywords/lasso","display_name":"Lasso (programming language)","score":0.4254012703895569},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3753841817378998},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3407660126686096},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.33515045046806335},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.3135297894477844},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.22750824689865112}],"concepts":[{"id":"https://openalex.org/C179690561","wikidata":"https://www.wikidata.org/wiki/Q4316110","display_name":"Underdetermined system","level":2,"score":0.6633778810501099},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.6201549172401428},{"id":"https://openalex.org/C70958404","wikidata":"https://www.wikidata.org/wiki/Q7512728","display_name":"Signal reconstruction","level":4,"score":0.6094040870666504},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6046527028083801},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.599183976650238},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.5222386121749878},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.5208562016487122},{"id":"https://openalex.org/C37616216","wikidata":"https://www.wikidata.org/wiki/Q3218363","display_name":"Lasso (programming language)","level":2,"score":0.4254012703895569},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3753841817378998},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3407660126686096},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.33515045046806335},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.3135297894477844},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.22750824689865112},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/acssc.2014.7094749","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acssc.2014.7094749","pdf_url":null,"source":{"id":"https://openalex.org/S4363608593","display_name":"2014 48th Asilomar Conference on Signals, Systems and Computers","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"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":"2014 48th Asilomar Conference on Signals, Systems and Computers","raw_type":"proceedings-article"},{"id":"pmh:oai:lib.dr.iastate.edu:ece_conf-1003","is_oa":false,"landing_page_url":"https://lib.dr.iastate.edu/ece_conf/4","pdf_url":null,"source":{"id":"https://openalex.org/S4377196104","display_name":"Iowa State University Digital Repository (Iowa State University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I173911158","host_organization_name":"Iowa State University","host_organization_lineage":["https://openalex.org/I173911158"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Electrical and Computer Engineering Conference Papers, Posters and Presentations","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1590628445","https://openalex.org/W1824074430","https://openalex.org/W2004574300","https://openalex.org/W2022611944","https://openalex.org/W2030161963","https://openalex.org/W2037521346","https://openalex.org/W2038194450","https://openalex.org/W2050892949","https://openalex.org/W2056636001","https://openalex.org/W2096180865","https://openalex.org/W2100556411","https://openalex.org/W2109449402","https://openalex.org/W2126607811","https://openalex.org/W2127447444","https://openalex.org/W2163916252","https://openalex.org/W2164278908","https://openalex.org/W2296616510","https://openalex.org/W2495595050","https://openalex.org/W2913535645","https://openalex.org/W2936995161","https://openalex.org/W2962867031","https://openalex.org/W3098745759","https://openalex.org/W3106237033","https://openalex.org/W4250955649","https://openalex.org/W4292363360","https://openalex.org/W6660083201","https://openalex.org/W6758920291","https://openalex.org/W6761030284"],"related_works":["https://openalex.org/W2549922247","https://openalex.org/W2300663769","https://openalex.org/W1523391825","https://openalex.org/W2152231009","https://openalex.org/W1939631077","https://openalex.org/W2735239078","https://openalex.org/W2152589265","https://openalex.org/W2071589878","https://openalex.org/W2963414100","https://openalex.org/W2378166785"],"abstract_inverted_index":{"We":[0,47,159],"develop":[1,125],"a":[2,15,42,61,64,73,131],"fast":[3],"proximal":[4,109],"gradient":[5],"scheme":[6,129,134],"for":[7,137],"reconstructing":[8],"nonnegative":[9,38],"signals":[10],"that":[11,76,135],"are":[12],"sparse":[13],"in":[14],"transform":[16,93],"domain":[17],"from":[18],"underdetermined":[19],"measurements.":[20],"This":[21,95],"signal":[22,31,78,169,190],"model":[23],"is":[24,34,60,98,111],"motivated":[25],"by":[26,182],"tomographic":[27,176],"applications":[28],"where":[29,53,107],"the":[30,49,54,91,108,122,143,146,161,185,188,205],"of":[32,63,117,142,187,193],"interest":[33],"known":[35],"to":[36,57],"be":[37,58],"because":[39],"it":[40],"represents":[41],"tissue":[43],"or":[44],"material":[45],"density.":[46],"adopt":[48],"unconstrained":[50],"regularization":[51,74],"framework":[52],"objective":[55,96],"function":[56,97,105],"minimized":[59,99],"sum":[62],"convex":[65],"data":[66],"fidelity":[67],"(negative":[68],"log-likelihood":[69],"(NLL))":[70],"term":[71,75],"and":[72,80,130,153,167,175,179,191],"imposes":[77],"nonnegativity":[79,186],"sparsity":[81,192],"via":[82,100,113,172],"an":[83,126],"\u2113":[84],"<sub":[85],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[86],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">1</sub>":[87],"-norm":[88],"constraint":[89],"on":[90],"signal's":[92],"coefficients.":[94],"Nesterov's":[101],"proximal-gradient":[102],"method":[103,116],"with":[104],"restart,":[106],"mapping":[110],"computed":[112],"alternating":[114],"direction":[115],"multipliers":[118],"(ADMM).":[119],"To":[120],"accelerate":[121],"convergence,":[123],"we":[124,149,197],"adaptive":[127],"continuation":[128],"step-size":[132],"selection":[133],"accounts":[136],"varying":[138],"local":[139],"Lipschitz":[140],"constant":[141],"NLL.":[144],"In":[145],"numerical":[147],"examples,":[148],"consider":[150],"Gaussian":[151],"linear":[152,156],"Poisson":[154],"generalized":[155],"measurement":[157],"models.":[158],"compare":[160],"proposed":[162],"penalized":[163],"NLL":[164],"minimization":[165],"approach":[166],"existing":[168,206],"reconstruction":[170,177,202],"methods":[171],"compressed":[173],"sensing":[174],"experiments":[178],"demonstrate":[180],"that,":[181],"exploiting":[183],"both":[184],"underlying":[189],"its":[194],"wavelet":[195],"coefficients,":[196],"can":[198],"achieve":[199],"significantly":[200],"better":[201],"performance":[203],"than":[204],"methods.":[207]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":2},{"year":2015,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
