{"id":"https://openalex.org/W2092987133","doi":"https://doi.org/10.1109/globalsip.2014.7032155","title":"On the detection of sparse signals with sensor networks based on subspace pursuit","display_name":"On the detection of sparse signals with sensor networks based on subspace pursuit","publication_year":2014,"publication_date":"2014-12-01","ids":{"openalex":"https://openalex.org/W2092987133","doi":"https://doi.org/10.1109/globalsip.2014.7032155","mag":"2092987133"},"language":"en","primary_location":{"id":"doi:10.1109/globalsip.2014.7032155","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globalsip.2014.7032155","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 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/A5074407829","display_name":"Hao Zhang Gang Li","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hao Zhang Gang Li","raw_affiliation_strings":["Department of Electronic Engineering, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060356785","display_name":"Thakshila Wimalajeewa","orcid":"https://orcid.org/0000-0003-3302-7851"},"institutions":[{"id":"https://openalex.org/I70983195","display_name":"Syracuse University","ror":"https://ror.org/025r5qe02","country_code":"US","type":"education","lineage":["https://openalex.org/I70983195"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Thakshila Wimalajeewa","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, Syracuse University, Syracuse, NY, United States"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, Syracuse University, Syracuse, NY, United States","institution_ids":["https://openalex.org/I70983195"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018292481","display_name":"Pramod K. Varshney","orcid":"https://orcid.org/0000-0003-4504-5088"},"institutions":[{"id":"https://openalex.org/I70983195","display_name":"Syracuse University","ror":"https://ror.org/025r5qe02","country_code":"US","type":"education","lineage":["https://openalex.org/I70983195"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Pramod K. Varshney","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, Syracuse University, Syracuse, NY, United States"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, Syracuse University, Syracuse, NY, United States","institution_ids":["https://openalex.org/I70983195"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5074407829"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":2.2076,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":{"value":0.86866536,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"438","last_page":"442"},"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/T11447","display_name":"Blind Source Separation Techniques","score":0.998199999332428,"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/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9980999827384949,"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/computer-science","display_name":"Computer science","score":0.7315643429756165},{"id":"https://openalex.org/keywords/fusion-center","display_name":"Fusion center","score":0.6872836947441101},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.5885058045387268},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.5668460130691528},{"id":"https://openalex.org/keywords/greedy-algorithm","display_name":"Greedy algorithm","score":0.5266846418380737},{"id":"https://openalex.org/keywords/bandwidth","display_name":"Bandwidth (computing)","score":0.490669846534729},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.47265660762786865},{"id":"https://openalex.org/keywords/wireless-sensor-network","display_name":"Wireless sensor network","score":0.4608568251132965},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.44336998462677},{"id":"https://openalex.org/keywords/distributed-algorithm","display_name":"Distributed algorithm","score":0.4206133186817169},{"id":"https://openalex.org/keywords/matching-pursuit","display_name":"Matching pursuit","score":0.4140494465827942},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.41316795349121094},{"id":"https://openalex.org/keywords/detection-theory","display_name":"Detection theory","score":0.4121581017971039},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.41055870056152344},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.31495583057403564},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2784498929977417},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.15465468168258667},{"id":"https://openalex.org/keywords/cognitive-radio","display_name":"Cognitive radio","score":0.14452102780342102},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.12408241629600525}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7315643429756165},{"id":"https://openalex.org/C2781234732","wikidata":"https://www.wikidata.org/wiki/Q943505","display_name":"Fusion center","level":4,"score":0.6872836947441101},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.5885058045387268},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.5668460130691528},{"id":"https://openalex.org/C51823790","wikidata":"https://www.wikidata.org/wiki/Q504353","display_name":"Greedy algorithm","level":2,"score":0.5266846418380737},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.490669846534729},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.47265660762786865},{"id":"https://openalex.org/C24590314","wikidata":"https://www.wikidata.org/wiki/Q336038","display_name":"Wireless sensor network","level":2,"score":0.4608568251132965},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.44336998462677},{"id":"https://openalex.org/C130120984","wikidata":"https://www.wikidata.org/wiki/Q2835898","display_name":"Distributed algorithm","level":2,"score":0.4206133186817169},{"id":"https://openalex.org/C156872377","wikidata":"https://www.wikidata.org/wiki/Q6786281","display_name":"Matching pursuit","level":3,"score":0.4140494465827942},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.41316795349121094},{"id":"https://openalex.org/C137270730","wikidata":"https://www.wikidata.org/wiki/Q120811","display_name":"Detection theory","level":3,"score":0.4121581017971039},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.41055870056152344},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.31495583057403564},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2784498929977417},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.15465468168258667},{"id":"https://openalex.org/C149946192","wikidata":"https://www.wikidata.org/wiki/Q3235733","display_name":"Cognitive radio","level":3,"score":0.14452102780342102},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.12408241629600525},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/globalsip.2014.7032155","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globalsip.2014.7032155","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE Global Conference on Signal and Information Processing (GlobalSIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6800000071525574,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W2005768446","https://openalex.org/W2043724336","https://openalex.org/W2063056388","https://openalex.org/W2105017647","https://openalex.org/W2115144080","https://openalex.org/W2119717304","https://openalex.org/W2123015311","https://openalex.org/W2130998683","https://openalex.org/W2138953932","https://openalex.org/W2160979406","https://openalex.org/W2171959453","https://openalex.org/W2171974671"],"related_works":["https://openalex.org/W2011611369","https://openalex.org/W4297791310","https://openalex.org/W4372266926","https://openalex.org/W4245251483","https://openalex.org/W1998873033","https://openalex.org/W2116148865","https://openalex.org/W2279123345","https://openalex.org/W2366556501","https://openalex.org/W2965458591","https://openalex.org/W1520740474"],"abstract_inverted_index":{"In":[0,63],"this":[1],"paper,":[2],"we":[3],"consider":[4],"the":[5,64,73,78,113,128,134],"problem":[6],"of":[7,10,28,43,60,106,121,130],"distributed":[8,33,53,58],"detection":[9,27,59,105],"sparse":[11,29,61,74,107],"signals":[12,30,108],"with":[13,116],"a":[14,32,49,85,89,97,117],"sensor":[15],"network.":[16],"Due":[17],"to":[18,88,95,133],"practical":[19],"constraints":[20],"on":[21],"communication":[22,44],"bandwidth":[23],"and":[24,45,83],"computational":[25],"capacity,":[26],"in":[31,41],"manner":[34],"is":[35],"more":[36],"efficient":[37],"than":[38],"centralized":[39],"processing":[40],"terms":[42],"computation.":[46],"We":[47,125],"develop":[48],"greedy":[50],"algorithm":[51,82],"named":[52],"subspace":[54,79],"pursuit":[55,80],"(DSP)":[56],"for":[57,72],"signals.":[62],"proposed":[65,114],"approach,":[66],"each":[67,93],"node":[68],"computes":[69],"an":[70],"estimate":[71],"support":[75],"iteratively":[76],"using":[77],"(SP)":[81],"transmits":[84],"condensed":[86],"message":[87],"fusion":[90],"center":[91],"during":[92],"iteration":[94],"compute":[96],"decision":[98],"statistic.":[99],"Experimental":[100],"results":[101],"show":[102],"that":[103],"reliable":[104],"can":[109],"be":[110],"obtained":[111],"by":[112],"approach":[115],"very":[118],"small":[119],"number":[120],"iterations":[122],"per":[123],"node.":[124],"further":[126],"demonstrate":[127],"superiority":[129],"our":[131],"algorithms":[132],"most":[135],"related":[136],"sparsity-driven":[137],"methods.":[138]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":5},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}