{"id":"https://openalex.org/W1991031161","doi":"https://doi.org/10.1109/icassp.2014.6854226","title":"Complex multitask Bayesian compressive sensing","display_name":"Complex multitask Bayesian compressive sensing","publication_year":2014,"publication_date":"2014-05-01","ids":{"openalex":"https://openalex.org/W1991031161","doi":"https://doi.org/10.1109/icassp.2014.6854226","mag":"1991031161"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2014.6854226","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2014.6854226","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5076758349","display_name":"Qisong Wu","orcid":"https://orcid.org/0000-0002-2114-7672"},"institutions":[{"id":"https://openalex.org/I7863295","display_name":"Villanova University","ror":"https://ror.org/02g7kd627","country_code":"US","type":"education","lineage":["https://openalex.org/I7863295"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qisong Wu","raw_affiliation_strings":["Center for Advanced Communications, Villanova University, Villanova, PA, USA","Center for Advanced Communication, Villanova University, Villanova, PA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Advanced Communications, Villanova University, Villanova, PA, USA","institution_ids":["https://openalex.org/I7863295"]},{"raw_affiliation_string":"Center for Advanced Communication, Villanova University, Villanova, PA, USA","institution_ids":["https://openalex.org/I7863295"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074195801","display_name":"Yimin D. Zhang","orcid":"https://orcid.org/0000-0002-4625-209X"},"institutions":[{"id":"https://openalex.org/I7863295","display_name":"Villanova University","ror":"https://ror.org/02g7kd627","country_code":"US","type":"education","lineage":["https://openalex.org/I7863295"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yimin D. Zhang","raw_affiliation_strings":["Center for Advanced Communications, Villanova University, Villanova, PA, USA","Center for Advanced Communication, Villanova University, Villanova, PA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Advanced Communications, Villanova University, Villanova, PA, USA","institution_ids":["https://openalex.org/I7863295"]},{"raw_affiliation_string":"Center for Advanced Communication, Villanova University, Villanova, PA, USA","institution_ids":["https://openalex.org/I7863295"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007661434","display_name":"Moeness G. Amin","orcid":"https://orcid.org/0000-0002-0926-4120"},"institutions":[{"id":"https://openalex.org/I7863295","display_name":"Villanova University","ror":"https://ror.org/02g7kd627","country_code":"US","type":"education","lineage":["https://openalex.org/I7863295"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Moeness G. Amin","raw_affiliation_strings":["Center for Advanced Communications, Villanova University, Villanova, PA, USA","Center for Advanced Communication, Villanova University, Villanova, PA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Advanced Communications, Villanova University, Villanova, PA, USA","institution_ids":["https://openalex.org/I7863295"]},{"raw_affiliation_string":"Center for Advanced Communication, Villanova University, Villanova, PA, USA","institution_ids":["https://openalex.org/I7863295"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012490058","display_name":"Braham Himed","orcid":"https://orcid.org/0000-0003-0053-6270"},"institutions":[{"id":"https://openalex.org/I1280414376","display_name":"United States Air Force Research Laboratory","ror":"https://ror.org/02e2egq70","country_code":"US","type":"facility","lineage":["https://openalex.org/I1280414376","https://openalex.org/I1330347796","https://openalex.org/I4210102105","https://openalex.org/I4389425425"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Braham Himed","raw_affiliation_strings":["RF Technology Branch, WPAFB, OH, USA","RF Technol. Branch, Air Force Res. Lab. (AFRL/RYMD), Wright-Patterson AFB, OH, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"RF Technology Branch, WPAFB, OH, USA","institution_ids":[]},{"raw_affiliation_string":"RF Technol. Branch, Air Force Res. Lab. (AFRL/RYMD), Wright-Patterson AFB, OH, USA","institution_ids":["https://openalex.org/I1280414376"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":31.8069,"has_fulltext":false,"cited_by_count":122,"citation_normalized_percentile":{"value":0.99910839,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"3375","last_page":"3379"},"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":0.9991000294685364,"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/T11739","display_name":"Microwave Imaging and Scattering Analysis","score":0.9973000288009644,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.8363544344902039},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5778473615646362},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5668892860412598},{"id":"https://openalex.org/keywords/lasso","display_name":"Lasso (programming language)","score":0.5488319396972656},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5237455368041992},{"id":"https://openalex.org/keywords/signal-recovery","display_name":"Signal recovery","score":0.4748380780220032},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.43509641289711},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41848224401474},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32708513736724854}],"concepts":[{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.8363544344902039},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5778473615646362},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5668892860412598},{"id":"https://openalex.org/C37616216","wikidata":"https://www.wikidata.org/wiki/Q3218363","display_name":"Lasso (programming language)","level":2,"score":0.5488319396972656},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5237455368041992},{"id":"https://openalex.org/C2989281035","wikidata":"https://www.wikidata.org/wiki/Q120811","display_name":"Signal recovery","level":3,"score":0.4748380780220032},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.43509641289711},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41848224401474},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32708513736724854},{"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/icassp.2014.6854226","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2014.6854226","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.709.2991","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.709.2991","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://yiminzhang.com/pdf/icassp14_qw.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/1","display_name":"No poverty","score":0.5899999737739563}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W427416012","https://openalex.org/W1591116419","https://openalex.org/W1974718273","https://openalex.org/W1988922258","https://openalex.org/W1996049583","https://openalex.org/W2071284784","https://openalex.org/W2077964948","https://openalex.org/W2085835372","https://openalex.org/W2085910483","https://openalex.org/W2096732023","https://openalex.org/W2127271355","https://openalex.org/W2128439740","https://openalex.org/W2135046866","https://openalex.org/W2138019504","https://openalex.org/W2140367840","https://openalex.org/W2142653080","https://openalex.org/W2145856765","https://openalex.org/W2164725201","https://openalex.org/W2167604521","https://openalex.org/W2296616510","https://openalex.org/W2511885285","https://openalex.org/W2911546748","https://openalex.org/W4235713725","https://openalex.org/W4250955649","https://openalex.org/W4285719527","https://openalex.org/W6643969875","https://openalex.org/W6674776011"],"related_works":["https://openalex.org/W2106867672","https://openalex.org/W2986034714","https://openalex.org/W1500257147","https://openalex.org/W2766602233","https://openalex.org/W2964128238","https://openalex.org/W2374064591","https://openalex.org/W1542882895","https://openalex.org/W2058918977","https://openalex.org/W2804422224","https://openalex.org/W2145767695"],"abstract_inverted_index":{"An":[0],"effective":[1,121],"complex":[2,17,44,52,122,130],"multitask":[3,21],"Bayesian":[4,22],"compressive":[5,23],"sensing":[6,24,40],"(CMT-BCS)":[7],"algorithm":[8,26,86,102,119],"is":[9,27],"proposed":[10,117],"to":[11],"recover":[12],"sparse":[13,16,33,123],"or":[14],"group":[15,66,131],"signals.":[18],"The":[19,116],"existing":[20],"(MT-CS)":[25],"powerful":[28],"in":[29],"recovering":[30],"multiple":[31],"real-valued":[32],"solutions.":[34],"However,":[35],"a":[36,51,98,112],"large":[37],"class":[38],"of":[39,68,106],"problems":[41],"deal":[42],"with":[43],"values.":[45],"A":[46],"simple":[47],"approach,":[48],"which":[49],"decomposes":[50],"value":[53],"into":[54,63],"independent":[55],"real":[56,91],"and":[57,72,92,95,100,126,129],"imaginary":[58,93],"components,":[59,94],"does":[60],"not":[61],"take":[62],"account":[64],"the":[65,84,90,104,107],"sparsity":[67],"these":[69],"two":[70],"components":[71],"thus":[73],"yields":[74],"poor":[75],"recovery":[76,125],"performance.":[77],"In":[78],"this":[79],"paper,":[80],"we":[81],"first":[82],"introduce":[83],"CMT-BCS":[85,118],"that":[87],"jointly":[88],"treats":[89],"then":[96],"derive":[97],"fast":[99],"accurate":[101],"for":[103],"estimation":[105],"prior":[108],"parameters":[109],"by":[110],"solving":[111],"surrogate":[113],"convex":[114],"function.":[115],"achieves":[120],"signal":[124],"outperforms":[127],"MT-CS":[128],"Lasso.":[132]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":13},{"year":2021,"cited_by_count":9},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":10},{"year":2018,"cited_by_count":8},{"year":2017,"cited_by_count":9},{"year":2016,"cited_by_count":14},{"year":2015,"cited_by_count":23},{"year":2014,"cited_by_count":13}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
