{"id":"https://openalex.org/W2921832454","doi":"https://doi.org/10.23919/apsipa.2018.8659457","title":"Variational Bayesian Compressed Sensing for Sparse and Locally Constant Signals","display_name":"Variational Bayesian Compressed Sensing for Sparse and Locally Constant Signals","publication_year":2018,"publication_date":"2018-11-01","ids":{"openalex":"https://openalex.org/W2921832454","doi":"https://doi.org/10.23919/apsipa.2018.8659457","mag":"2921832454"},"language":"en","primary_location":{"id":"doi:10.23919/apsipa.2018.8659457","is_oa":false,"landing_page_url":"https://doi.org/10.23919/apsipa.2018.8659457","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)","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/A5004624497","display_name":"Shunsuke Horii","orcid":null},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Shunsuke Horii","raw_affiliation_strings":["Waseda University, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Waseda University, Tokyo, Japan","institution_ids":["https://openalex.org/I150744194"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5004624497"],"corresponding_institution_ids":["https://openalex.org/I150744194"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.20571704,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"972","last_page":"976"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9970999956130981,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.996399998664856,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.8500466346740723},{"id":"https://openalex.org/keywords/basis-pursuit","display_name":"Basis pursuit","score":0.7663978338241577},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.6104287505149841},{"id":"https://openalex.org/keywords/basis-function","display_name":"Basis function","score":0.5909283757209778},{"id":"https://openalex.org/keywords/basis","display_name":"Basis (linear algebra)","score":0.5577650666236877},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5466062426567078},{"id":"https://openalex.org/keywords/norm","display_name":"Norm (philosophy)","score":0.5438566207885742},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.49715736508369446},{"id":"https://openalex.org/keywords/signal-reconstruction","display_name":"Signal reconstruction","score":0.4598556160926819},{"id":"https://openalex.org/keywords/optimization-problem","display_name":"Optimization problem","score":0.4458942711353302},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.4105263948440552},{"id":"https://openalex.org/keywords/matching-pursuit","display_name":"Matching pursuit","score":0.3775371015071869},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3514230251312256},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3103552460670471}],"concepts":[{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.8500466346740723},{"id":"https://openalex.org/C99217422","wikidata":"https://www.wikidata.org/wiki/Q4867576","display_name":"Basis pursuit","level":4,"score":0.7663978338241577},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6104287505149841},{"id":"https://openalex.org/C5917680","wikidata":"https://www.wikidata.org/wiki/Q2621825","display_name":"Basis function","level":2,"score":0.5909283757209778},{"id":"https://openalex.org/C12426560","wikidata":"https://www.wikidata.org/wiki/Q189569","display_name":"Basis (linear algebra)","level":2,"score":0.5577650666236877},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5466062426567078},{"id":"https://openalex.org/C191795146","wikidata":"https://www.wikidata.org/wiki/Q3878446","display_name":"Norm (philosophy)","level":2,"score":0.5438566207885742},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.49715736508369446},{"id":"https://openalex.org/C70958404","wikidata":"https://www.wikidata.org/wiki/Q7512728","display_name":"Signal reconstruction","level":4,"score":0.4598556160926819},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.4458942711353302},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.4105263948440552},{"id":"https://openalex.org/C156872377","wikidata":"https://www.wikidata.org/wiki/Q6786281","display_name":"Matching pursuit","level":3,"score":0.3775371015071869},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3514230251312256},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3103552460670471},{"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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/apsipa.2018.8659457","is_oa":false,"landing_page_url":"https://doi.org/10.23919/apsipa.2018.8659457","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)","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":16,"referenced_works":["https://openalex.org/W33731299","https://openalex.org/W1601795611","https://openalex.org/W1663973292","https://openalex.org/W1760895834","https://openalex.org/W1970554427","https://openalex.org/W1976365540","https://openalex.org/W1977252496","https://openalex.org/W1982652137","https://openalex.org/W2071284784","https://openalex.org/W2078204800","https://openalex.org/W2101675075","https://openalex.org/W2107710506","https://openalex.org/W2136477614","https://openalex.org/W2146571341","https://openalex.org/W2164129707","https://openalex.org/W6676234565"],"related_works":["https://openalex.org/W2378166785","https://openalex.org/W2169904627","https://openalex.org/W2382972663","https://openalex.org/W2388133936","https://openalex.org/W2436826437","https://openalex.org/W2340242818","https://openalex.org/W2103001330","https://openalex.org/W2465351041","https://openalex.org/W2241396314","https://openalex.org/W2946877649"],"abstract_inverted_index":{"In":[0,164],"this":[1,165],"paper,":[2,166],"we":[3,167,196],"deal":[4],"with":[5],"the":[6,15,19,54,64,68,77,89,101,105,111,116,119,123,126,137,146,153,161,177,183,188,191,199,203,217,230],"signal":[7,21,69,107,127,178,205],"recovery":[8,60,179,224],"problem":[9,16,102],"in":[10,73,128,151],"compressed":[11,218,231],"sensing,":[12],"that":[13,62,79,143,172,195,210],"is,":[14],"of":[17,53,67,96,118,122,125,136,187,190,202,229],"estimating":[18],"original":[20,106,204],"from":[22],"its":[23,71,80],"linear":[24,81],"measurements.":[25],"Recovery":[26],"algorithms":[27,37,98],"can":[28,140,197,212],"be":[29,141,149,213],"mainly":[30],"classified":[31],"into":[32],"two":[33],"types,":[34],"optimization":[35,58],"based":[36,41,59,181],"and":[38,131,157,176,206,226],"statistical":[39,170,192],"modeling":[40],"algorithms.":[42],"Basis":[43],"pursuit":[44,48],"(BP)":[45],"or":[46,70,86],"basis":[47,75,130],"denoising":[49],"(BPDN)":[50],"is":[51,83,108,114,194,208],"one":[52],"most":[55],"widely":[56],"used":[57,214],"algorithms,":[61],"minimizes":[63],"l1":[65,120],"norm":[66,121],"coefficients":[72,124],"some":[74,129],"under":[76],"constraint":[78],"transform":[82,155],"equal":[84],"to":[85,88,148,215],"close":[87],"observation":[90],"signal.":[91],"There":[92],"are":[93,234],"various":[94],"extensions":[95],"those":[97,174],"depending":[99],"on":[100,182,236],"structure.":[103],"When":[104],"an":[109],"image,":[110],"objective":[112],"function":[113],"often":[115],"sum":[117],"a":[132,169],"total":[133],"variation":[134],"(TV)":[135],"image.":[138],"It":[139],"considered":[142],"it":[144,207,211],"requires":[145],"image":[147],"sparse":[150],"both":[152],"specific":[154],"domain":[156],"finite":[158],"differences":[159],"at":[160],"same":[162],"time.":[163],"propose":[168],"model":[171],"represents":[173],"sparsities":[175],"algorithm":[180,225],"variational":[184],"method.":[185],"One":[186],"advantages":[189],"approach":[193],"utilize":[198],"posterior":[200],"information":[201],"known":[209],"construct":[216],"sensing":[219,232],"measurements":[220,233],"adaptively.":[221],"The":[222],"proposed":[223],"adaptive":[227],"construction":[228],"validated":[235],"numerical":[237],"experiments.":[238]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}