{"id":"https://openalex.org/W2963889596","doi":"https://doi.org/10.1109/glocom.2017.8254836","title":"Sparse Vector Recovery: Bernoulli-Gaussian Message Passing","display_name":"Sparse Vector Recovery: Bernoulli-Gaussian Message Passing","publication_year":2017,"publication_date":"2017-12-01","ids":{"openalex":"https://openalex.org/W2963889596","doi":"https://doi.org/10.1109/glocom.2017.8254836","mag":"2963889596"},"language":"en","primary_location":{"id":"doi:10.1109/glocom.2017.8254836","is_oa":false,"landing_page_url":"https://doi.org/10.1109/glocom.2017.8254836","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"GLOBECOM 2017 - 2017 IEEE Global Communications Conference","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/A5089831302","display_name":"Lei Liu","orcid":"https://orcid.org/0000-0002-0807-2135"},"institutions":[{"id":"https://openalex.org/I152815399","display_name":"Singapore University of Technology and Design","ror":"https://ror.org/05j6fvn87","country_code":"SG","type":"education","lineage":["https://openalex.org/I152815399"]},{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN","SG"],"is_corresponding":true,"raw_author_name":"Lei Liu","raw_affiliation_strings":["Singapore University of Technology and Design, Singapore","State Key Lab of ISN, Xidian University, China"],"affiliations":[{"raw_affiliation_string":"Singapore University of Technology and Design, Singapore","institution_ids":["https://openalex.org/I152815399"]},{"raw_affiliation_string":"State Key Lab of ISN, Xidian University, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076730859","display_name":"Chongwen Huang","orcid":"https://orcid.org/0000-0001-8398-8437"},"institutions":[{"id":"https://openalex.org/I152815399","display_name":"Singapore University of Technology and Design","ror":"https://ror.org/05j6fvn87","country_code":"SG","type":"education","lineage":["https://openalex.org/I152815399"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Chongwen Huang","raw_affiliation_strings":["Singapore University of Technology and Design, Singapore"],"affiliations":[{"raw_affiliation_string":"Singapore University of Technology and Design, Singapore","institution_ids":["https://openalex.org/I152815399"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012222793","display_name":"Yuhao Chi","orcid":"https://orcid.org/0000-0001-9850-0246"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]},{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN","SG"],"is_corresponding":false,"raw_author_name":"Yuhao Chi","raw_affiliation_strings":["Nanyang Technological University, Singapore","State Key Lab of ISN, Xidian University, China"],"affiliations":[{"raw_affiliation_string":"Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]},{"raw_affiliation_string":"State Key Lab of ISN, Xidian University, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060020877","display_name":"Chau Yuen","orcid":"https://orcid.org/0000-0002-9307-2120"},"institutions":[{"id":"https://openalex.org/I152815399","display_name":"Singapore University of Technology and Design","ror":"https://ror.org/05j6fvn87","country_code":"SG","type":"education","lineage":["https://openalex.org/I152815399"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Chau Yuen","raw_affiliation_strings":["Singapore University of Technology and Design, Singapore"],"affiliations":[{"raw_affiliation_string":"Singapore University of Technology and Design, Singapore","institution_ids":["https://openalex.org/I152815399"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100763983","display_name":"Yong Liang Guan","orcid":"https://orcid.org/0000-0002-9757-630X"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Yong Liang Guan","raw_affiliation_strings":["Nanyang Technological University, Singapore"],"affiliations":[{"raw_affiliation_string":"Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100414362","display_name":"Ying Li","orcid":"https://orcid.org/0000-0002-9604-2664"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ying Li","raw_affiliation_strings":["State Key Lab of ISN, Xidian University, China"],"affiliations":[{"raw_affiliation_string":"State Key Lab of ISN, Xidian University, China","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5089831302"],"corresponding_institution_ids":["https://openalex.org/I149594827","https://openalex.org/I152815399"],"apc_list":null,"apc_paid":null,"fwci":2.4009,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.88614187,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9995999932289124,"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"}},{"id":"https://openalex.org/T11233","display_name":"Advanced Adaptive Filtering Techniques","score":0.9986000061035156,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.6759195923805237},{"id":"https://openalex.org/keywords/bernoullis-principle","display_name":"Bernoulli's principle","score":0.6539312601089478},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.6330376863479614},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.6176429986953735},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6114442944526672},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.6032038927078247},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.6004883050918579},{"id":"https://openalex.org/keywords/message-passing","display_name":"Message passing","score":0.5122262835502625},{"id":"https://openalex.org/keywords/minimum-mean-square-error","display_name":"Minimum mean square error","score":0.5015387535095215},{"id":"https://openalex.org/keywords/position","display_name":"Position (finance)","score":0.4964612126350403},{"id":"https://openalex.org/keywords/word-error-rate","display_name":"Word error rate","score":0.4807838797569275},{"id":"https://openalex.org/keywords/value","display_name":"Value (mathematics)","score":0.46774083375930786},{"id":"https://openalex.org/keywords/upper-and-lower-bounds","display_name":"Upper and lower bounds","score":0.45061200857162476},{"id":"https://openalex.org/keywords/gaussian-noise","display_name":"Gaussian noise","score":0.4384320378303528},{"id":"https://openalex.org/keywords/bit-error-rate","display_name":"Bit error rate","score":0.43040403723716736},{"id":"https://openalex.org/keywords/rate-of-convergence","display_name":"Rate of convergence","score":0.4185335040092468},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.41689518094062805},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.29503193497657776},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.2614583373069763},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.2579830288887024},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.13337993621826172},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.11290571093559265},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.10939103364944458},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.0777825117111206},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.07259640097618103}],"concepts":[{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.6759195923805237},{"id":"https://openalex.org/C152361515","wikidata":"https://www.wikidata.org/wiki/Q181328","display_name":"Bernoulli's principle","level":2,"score":0.6539312601089478},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.6330376863479614},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6176429986953735},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6114442944526672},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.6032038927078247},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.6004883050918579},{"id":"https://openalex.org/C854659","wikidata":"https://www.wikidata.org/wiki/Q1859284","display_name":"Message passing","level":2,"score":0.5122262835502625},{"id":"https://openalex.org/C90652560","wikidata":"https://www.wikidata.org/wiki/Q11091747","display_name":"Minimum mean square error","level":3,"score":0.5015387535095215},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.4964612126350403},{"id":"https://openalex.org/C40969351","wikidata":"https://www.wikidata.org/wiki/Q3516228","display_name":"Word error rate","level":2,"score":0.4807838797569275},{"id":"https://openalex.org/C2776291640","wikidata":"https://www.wikidata.org/wiki/Q2912517","display_name":"Value (mathematics)","level":2,"score":0.46774083375930786},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.45061200857162476},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.4384320378303528},{"id":"https://openalex.org/C56296756","wikidata":"https://www.wikidata.org/wiki/Q840922","display_name":"Bit error rate","level":3,"score":0.43040403723716736},{"id":"https://openalex.org/C57869625","wikidata":"https://www.wikidata.org/wiki/Q1783502","display_name":"Rate of convergence","level":3,"score":0.4185335040092468},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.41689518094062805},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.29503193497657776},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.2614583373069763},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.2579830288887024},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.13337993621826172},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.11290571093559265},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.10939103364944458},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0777825117111206},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.07259640097618103},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/glocom.2017.8254836","is_oa":false,"landing_page_url":"https://doi.org/10.1109/glocom.2017.8254836","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"GLOBECOM 2017 - 2017 IEEE Global Communications Conference","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":28,"referenced_works":["https://openalex.org/W340244495","https://openalex.org/W2000828982","https://openalex.org/W2026933032","https://openalex.org/W2028781966","https://openalex.org/W2072184935","https://openalex.org/W2082029531","https://openalex.org/W2098012923","https://openalex.org/W2101279388","https://openalex.org/W2139053635","https://openalex.org/W2160051394","https://openalex.org/W2164452299","https://openalex.org/W2166670884","https://openalex.org/W2281640263","https://openalex.org/W2296616510","https://openalex.org/W2467524786","https://openalex.org/W2562244919","https://openalex.org/W2603333836","https://openalex.org/W2962941466","https://openalex.org/W2962965594","https://openalex.org/W2963896647","https://openalex.org/W3100688274","https://openalex.org/W3103471669","https://openalex.org/W3121195152","https://openalex.org/W4248709896","https://openalex.org/W4250955649","https://openalex.org/W4300263211","https://openalex.org/W6675452673","https://openalex.org/W6727682202"],"related_works":["https://openalex.org/W2978729728","https://openalex.org/W1619264321","https://openalex.org/W2899588557","https://openalex.org/W4254565718","https://openalex.org/W4298392611","https://openalex.org/W3094386089","https://openalex.org/W2180382450","https://openalex.org/W2129020938","https://openalex.org/W4288966080","https://openalex.org/W2767174816"],"abstract_inverted_index":{"Low-cost":[0],"message":[1],"passing":[2],"(MP)":[3],"algorithm":[4],"has":[5],"been":[6],"recognized":[7],"as":[8,66,68],"a":[9,94],"promising":[10],"technique":[11],"for":[12,100],"sparse":[13,44],"vector":[14],"recovery.":[15,71],"However,":[16],"the":[17,29,34,43,63,69,74,101,106,131],"existing":[18],"MP":[19,57],"algorithms":[20],"either":[21],"focus":[22],"on":[23],"mean":[24],"square":[25],"error":[26,39],"(MSE)":[27],"of":[28,42,103,133,137],"value":[30,64],"recovery":[31,48,65],"while":[32,49],"ignoring":[33,50],"sparsity":[35],"requirement,":[36],"or":[37],"support":[38,45,70],"rate":[40],"(SER)":[41],"(non-zero":[46],"position)":[47],"its":[51],"value.":[52],"A":[53],"novel":[54],"low-complexity":[55],"Bernoulli-Gaussian":[56],"(BGMP)":[58],"is":[59,98,116],"proposed":[60,75],"to":[61,118,129],"perform":[62],"well":[67],"Particularly,":[72],"in":[73,121,135],"BGMP,":[76],"support-related":[77],"Bernoulli":[78],"messages":[79,84],"and":[80,88,141],"value-":[81],"related":[82],"Gaussian":[83],"are":[85,127],"jointly":[86],"processed":[87],"assist":[89],"each":[90],"other.":[91],"In":[92],"addition,":[93],"strict":[95],"lower":[96,114],"bound":[97,115],"developed":[99],"MSE":[102],"BGMP":[104,134],"via":[105],"genie-aided":[107],"minimum":[108],"mean-square-error":[109],"(GA-MMSE)":[110],"method.":[111],"The":[112],"GA-MMSE":[113],"shown":[117],"be":[119],"tight":[120],"high":[122],"signal-to-noise":[123],"ratio.":[124],"Numerical":[125],"results":[126],"provided":[128],"verify":[130],"advantage":[132],"terms":[136],"final":[138],"MSE,":[139],"SER":[140],"convergence":[142],"speed.":[143]},"counts_by_year":[{"year":2023,"cited_by_count":3},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}