{"id":"https://openalex.org/W2539168774","doi":"https://doi.org/10.1109/globalsip.2016.7905845","title":"D-OAMP: A denoising-based signal recovery algorithm for compressed sensing","display_name":"D-OAMP: A denoising-based signal recovery algorithm for compressed sensing","publication_year":2016,"publication_date":"2016-12-01","ids":{"openalex":"https://openalex.org/W2539168774","doi":"https://doi.org/10.1109/globalsip.2016.7905845","mag":"2539168774"},"language":"en","primary_location":{"id":"doi:10.1109/globalsip.2016.7905845","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globalsip.2016.7905845","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE Global Conference on Signal and Information Processing (GlobalSIP)","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/A5102963573","display_name":"Zhipeng Xue","orcid":"https://orcid.org/0000-0001-6772-7368"},"institutions":[{"id":"https://openalex.org/I30809798","display_name":"ShanghaiTech University","ror":"https://ror.org/030bhh786","country_code":"CN","type":"education","lineage":["https://openalex.org/I30809798"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhipeng Xue","raw_affiliation_strings":["School of Information Science and Technology, ShanghaiTech University"],"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, ShanghaiTech University","institution_ids":["https://openalex.org/I30809798"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100687838","display_name":"Junjie Ma","orcid":"https://orcid.org/0000-0003-1263-5006"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Junjie Ma","raw_affiliation_strings":["Department of Electronic Engineering, City University of Hong Kong"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, City University of Hong Kong","institution_ids":["https://openalex.org/I168719708"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5063946480","display_name":"Xiaojun Yuan","orcid":"https://orcid.org/0000-0002-0433-6535"},"institutions":[{"id":"https://openalex.org/I30809798","display_name":"ShanghaiTech University","ror":"https://ror.org/030bhh786","country_code":"CN","type":"education","lineage":["https://openalex.org/I30809798"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaojun Yuan","raw_affiliation_strings":["School of Information Science and Technology, ShanghaiTech University"],"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, ShanghaiTech University","institution_ids":["https://openalex.org/I30809798"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5102963573"],"corresponding_institution_ids":["https://openalex.org/I30809798"],"apc_list":null,"apc_paid":null,"fwci":1.5198,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.81530166,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"267","last_page":"271"},"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9994999766349792,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9993000030517578,"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":0.8588913679122925},{"id":"https://openalex.org/keywords/recursion","display_name":"Recursion (computer science)","score":0.7087991237640381},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.6781864166259766},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.625254213809967},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.5792344212532043},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5528560876846313},{"id":"https://openalex.org/keywords/divergence","display_name":"Divergence (linguistics)","score":0.5285593271255493},{"id":"https://openalex.org/keywords/independent-and-identically-distributed-random-variables","display_name":"Independent and identically distributed random variables","score":0.47274813055992126},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.4336860775947571},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.43293625116348267},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2852718234062195},{"id":"https://openalex.org/keywords/random-variable","display_name":"Random variable","score":0.17889031767845154}],"concepts":[{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.8588913679122925},{"id":"https://openalex.org/C168773036","wikidata":"https://www.wikidata.org/wiki/Q264164","display_name":"Recursion (computer science)","level":2,"score":0.7087991237640381},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6781864166259766},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.625254213809967},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5792344212532043},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5528560876846313},{"id":"https://openalex.org/C207390915","wikidata":"https://www.wikidata.org/wiki/Q1230525","display_name":"Divergence (linguistics)","level":2,"score":0.5285593271255493},{"id":"https://openalex.org/C141513077","wikidata":"https://www.wikidata.org/wiki/Q378542","display_name":"Independent and identically distributed random variables","level":3,"score":0.47274813055992126},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.4336860775947571},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.43293625116348267},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2852718234062195},{"id":"https://openalex.org/C122123141","wikidata":"https://www.wikidata.org/wiki/Q176623","display_name":"Random variable","level":2,"score":0.17889031767845154},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0},{"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"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/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/globalsip.2016.7905845","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globalsip.2016.7905845","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE Global Conference on Signal and Information Processing (GlobalSIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W2000828982","https://openalex.org/W2003884262","https://openalex.org/W2011697680","https://openalex.org/W2018731202","https://openalex.org/W2034805741","https://openalex.org/W2054640142","https://openalex.org/W2082029531","https://openalex.org/W2140742952","https://openalex.org/W2219834096","https://openalex.org/W2603333836","https://openalex.org/W2610971674","https://openalex.org/W2963676935","https://openalex.org/W3098848552","https://openalex.org/W4250955649","https://openalex.org/W6651416709","https://openalex.org/W6735922532"],"related_works":["https://openalex.org/W2158224665","https://openalex.org/W2379589510","https://openalex.org/W1976679120","https://openalex.org/W2810730439","https://openalex.org/W4300044672","https://openalex.org/W4281614748","https://openalex.org/W1881631164","https://openalex.org/W2377519369","https://openalex.org/W2765883196","https://openalex.org/W3202311233"],"abstract_inverted_index":{"Approximate":[0],"message":[1],"passing":[2],"(AMP)":[3],"is":[4,44],"an":[5],"efficient":[6],"iterative":[7],"signal":[8],"recovery":[9,125],"algorithm":[10],"for":[11,84,106,127],"compressed":[12],"sensing":[13,16,93,130],"(CS).":[14],"For":[15],"matrices":[17,94],"with":[18],"independent":[19],"and":[20,104,124],"identically":[21],"distributed":[22],"(i.i.d.)":[23],"Gaussian":[24,89],"entries,":[25],"the":[26,55,68,79,99],"behavior":[27],"of":[28,47,81,101],"AMP":[29,42,48],"can":[30],"be":[31],"asymptotically":[32],"described":[33],"by":[34],"a":[35,45,51],"scaler":[36],"recursion":[37],"called":[38],"state":[39,76],"evolution.":[40],"Orthogonal":[41],"(OAMP)":[43],"variant":[46],"that":[49,75,116],"imposes":[50],"divergence-free":[52],"constraint":[53],"on":[54],"denoiser.":[56],"In":[57],"this":[58],"paper,":[59],"we":[60],"extend":[61],"OAMP":[62],"to":[63],"incorporate":[64],"generic":[65,85],"denoisers,":[66],"hence":[67],"name":[69],"D-OAMP.":[70],"Our":[71],"numerical":[72],"results":[73,114],"show":[74,115],"evolution":[77],"predicts":[78],"performance":[80],"D-OAMP":[82,105,117],"well":[83],"denoisers":[86],"when":[87],"i.i.d.":[88],"or":[90],"partial":[91,128],"orthogonal":[92,129],"are":[95],"involved.":[96],"We":[97],"compare":[98],"performances":[100],"denosing-AMP":[102],"(D-AMP)":[103],"recovering":[107],"natural":[108],"images":[109],"from":[110],"CS":[111],"measurements.":[112],"Simulation":[113],"outperforms":[118],"D-AMP":[119],"in":[120],"both":[121],"convergence":[122],"speed":[123],"accuracy":[126],"matrices.":[131]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}