{"id":"https://openalex.org/W2460547098","doi":"https://doi.org/10.1109/lsp.2016.2613898","title":"Double Detector for Sparse Signal Detection From One-Bit Compressed Sensing Measurements","display_name":"Double Detector for Sparse Signal Detection From One-Bit Compressed Sensing Measurements","publication_year":2016,"publication_date":"2016-09-27","ids":{"openalex":"https://openalex.org/W2460547098","doi":"https://doi.org/10.1109/lsp.2016.2613898","mag":"2460547098"},"language":"en","primary_location":{"id":"doi:10.1109/lsp.2016.2613898","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2016.2613898","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Signal Processing Letters","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1607.00494","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Hadi Zayyani","orcid":null},"institutions":[{"id":"https://openalex.org/I4210157736","display_name":"Qom University of Technology","ror":"https://ror.org/04zepk655","country_code":"IR","type":"education","lineage":["https://openalex.org/I4210157736"]}],"countries":["IR"],"is_corresponding":true,"raw_author_name":"Hadi Zayyani","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Qom University of Technology, Qom, Iran"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Qom University of Technology, Qom, Iran","institution_ids":["https://openalex.org/I4210157736"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Farzan Haddadi","orcid":null},"institutions":[{"id":"https://openalex.org/I67009956","display_name":"Iran University of Science and Technology","ror":"https://ror.org/01jw2p796","country_code":"IR","type":"education","lineage":["https://openalex.org/I67009956"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Farzan Haddadi","raw_affiliation_strings":["Department of Electrical Engineering, Iran University of Science and Technology, Tehran, Iran"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Iran University of Science and Technology, Tehran, Iran","institution_ids":["https://openalex.org/I67009956"]}]},{"author_position":"last","author":{"id":null,"display_name":"Mehdi Korki","orcid":null},"institutions":[{"id":"https://openalex.org/I57093077","display_name":"Swinburne University of Technology","ror":"https://ror.org/031rekg67","country_code":"AU","type":"education","lineage":["https://openalex.org/I57093077"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Mehdi Korki","raw_affiliation_strings":["School of Software and Electrical Engineering, Swinburne University of Technology, Melbourne, Vic, Australia"],"affiliations":[{"raw_affiliation_string":"School of Software and Electrical Engineering, Swinburne University of Technology, Melbourne, Vic, Australia","institution_ids":["https://openalex.org/I57093077"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210157736"],"apc_list":null,"apc_paid":null,"fwci":4.0491,"has_fulltext":false,"cited_by_count":37,"citation_normalized_percentile":{"value":0.9342914,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"23","issue":"11","first_page":"1637","last_page":"1641"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.7335000038146973,"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":0.7335000038146973,"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/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.23649999499320984,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10579","display_name":"Cognitive Radio Networks and Spectrum Sensing","score":0.0031999999191612005,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/detector","display_name":"Detector","score":0.8565999865531921},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.6409000158309937},{"id":"https://openalex.org/keywords/likelihood-ratio-test","display_name":"Likelihood-ratio test","score":0.5188000202178955},{"id":"https://openalex.org/keywords/detection-theory","display_name":"Detection theory","score":0.5182999968528748},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.5052000284194946},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.4413999915122986},{"id":"https://openalex.org/keywords/signal-to-noise-ratio","display_name":"Signal-to-noise ratio (imaging)","score":0.40059998631477356}],"concepts":[{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.8565999865531921},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.6409000158309937},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5306000113487244},{"id":"https://openalex.org/C9483764","wikidata":"https://www.wikidata.org/wiki/Q585740","display_name":"Likelihood-ratio test","level":2,"score":0.5188000202178955},{"id":"https://openalex.org/C137270730","wikidata":"https://www.wikidata.org/wiki/Q120811","display_name":"Detection theory","level":3,"score":0.5182999968528748},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.5052000284194946},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.462799996137619},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.4413999915122986},{"id":"https://openalex.org/C13944312","wikidata":"https://www.wikidata.org/wiki/Q7512748","display_name":"Signal-to-noise ratio (imaging)","level":2,"score":0.40059998631477356},{"id":"https://openalex.org/C57691317","wikidata":"https://www.wikidata.org/wiki/Q1289248","display_name":"Scalar (mathematics)","level":2,"score":0.3481000065803528},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.33709999918937683},{"id":"https://openalex.org/C139676723","wikidata":"https://www.wikidata.org/wiki/Q1193832","display_name":"Sign (mathematics)","level":2,"score":0.3294999897480011},{"id":"https://openalex.org/C55166926","wikidata":"https://www.wikidata.org/wiki/Q2892946","display_name":"Oracle","level":2,"score":0.32749998569488525},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3050000071525574},{"id":"https://openalex.org/C70958404","wikidata":"https://www.wikidata.org/wiki/Q7512728","display_name":"Signal reconstruction","level":4,"score":0.30410000681877136},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.29989999532699585},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.27799999713897705},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.27390000224113464},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.26269999146461487},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.25209999084472656}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/lsp.2016.2613898","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2016.2613898","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Signal Processing Letters","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1607.00494","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1607.00494","pdf_url":"https://arxiv.org/pdf/1607.00494","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:researchbank.swinburne.edu.au:6b38baed-04b1-426f-b1ed-2f1f307d9a8f/1","is_oa":false,"landing_page_url":"http://hdl.handle.net/1959.3/432328","pdf_url":null,"source":{"id":"https://openalex.org/S4306401157","display_name":"Swinburne Research Bank (Swinburne University of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I57093077","host_organization_name":"Swinburne University of Technology","host_organization_lineage":["https://openalex.org/I57093077"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Signal Processing Letters, Vol. 23, no. 11 (Nov 2016), pp. 1637-1641","raw_type":""}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1607.00494","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1607.00494","pdf_url":"https://arxiv.org/pdf/1607.00494","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W1978097885","https://openalex.org/W1983750483","https://openalex.org/W2008651162","https://openalex.org/W2027041980","https://openalex.org/W2060430274","https://openalex.org/W2073148077","https://openalex.org/W2080715720","https://openalex.org/W2098188576","https://openalex.org/W2112038498","https://openalex.org/W2113154139","https://openalex.org/W2114557042","https://openalex.org/W2115758294","https://openalex.org/W2121820607","https://openalex.org/W2129620001","https://openalex.org/W2129638195","https://openalex.org/W2135806093","https://openalex.org/W2140532408","https://openalex.org/W2144936371","https://openalex.org/W2148041990","https://openalex.org/W2154423986","https://openalex.org/W2160406955","https://openalex.org/W2963791893","https://openalex.org/W4250955649"],"related_works":[],"abstract_inverted_index":{"This":[0],"letter":[1],"presents":[2],"the":[3,17,31,35,43,69,90,93,104,147,151,157,162,167,170],"sparse":[4],"vector":[5,32],"signal":[6,24],"detection":[7,72,95],"from":[8],"one":[9],"bit":[10],"compressed":[11],"sensing":[12,145],"measurements,":[13],"in":[14,54,107],"contrast":[15],"to":[16,30,67,133,143],"previous":[18],"works":[19],"that":[20,85],"deal":[21],"with":[22,86],"scalar":[23],"detection.":[25],"Available":[26],"results":[27,83,148],"are":[28,47,79,149],"extended":[29],"case":[33],"and":[34,42,76,131,135,146],"generalized":[36],"likelihood":[37],"ratio":[38],"test":[39],"(GLRT)":[40],"detector":[41,60,140,164],"optimal":[44],"quantizer":[45,113],"design":[46,88,114],"obtained.":[48],"A":[49],"double-detector":[50,98],"scheme":[51,99],"is":[52,61,141],"introduced,":[53],"which":[55,155],"a":[56],"sensor":[57],"level":[58,65],"threshold":[59,91],"integrated":[62],"into":[63],"network":[64],"GLRT":[66,117],"improve":[68],"performance.":[70],"The":[71,138],"criteria":[73],"of":[74,89,97,169],"oracle":[75,134],"clairvoyant":[77,136],"detectors":[78],"also":[80],"derived.":[81],"Simulation":[82],"show":[84],"careful":[87],"detector,":[92,154],"overall":[94],"performance":[96],"would":[100],"be":[101],"better":[102],"than":[103],"sign-GLRT":[105],"proposed":[106,139,163],"[J.":[108],"Fang":[109],"et":[110],"al.,":[111],"\u201cOne-bit":[112],"for":[115],"multisensor":[116],"fusion,\u201d":[118],"IEEE":[119],"Signal":[120],"Process.":[121],"Lett.,":[122],"vol.":[123],"20,":[124],"no.":[125],"3,":[126],"pp.":[127],"257-260,":[128],"Mar.":[129],"2013]":[130],"close":[132],"detectors.":[137],"applied":[142],"spectrum":[144],"near":[150],"well-known":[152],"energy":[153],"uses":[156,166],"real":[158],"valued":[159],"data,":[160],"while":[161],"only":[165],"sign":[168],"data.":[171]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":9},{"year":2018,"cited_by_count":4}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2016-07-22T00:00:00"}
