{"id":"https://openalex.org/W2782220107","doi":"https://doi.org/10.1109/icspcc.2017.8242422","title":"A new distributed subspace pursuit algorithm and its performance analysis","display_name":"A new distributed subspace pursuit algorithm and its performance analysis","publication_year":2017,"publication_date":"2017-10-01","ids":{"openalex":"https://openalex.org/W2782220107","doi":"https://doi.org/10.1109/icspcc.2017.8242422","mag":"2782220107"},"language":"en","primary_location":{"id":"doi:10.1109/icspcc.2017.8242422","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icspcc.2017.8242422","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC)","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":null,"display_name":"Zhou Ming","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhou Ming","raw_affiliation_strings":["Air Force Early Warning Academy, Wu Han, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Air Force Early Warning Academy, Wu Han, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060768036","display_name":"Mingjiu Lv","orcid":"https://orcid.org/0000-0003-0515-6007"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lv Ming-jiu","raw_affiliation_strings":["No. three department, Air Force Early Warning Academy, Wu Han, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"No. three department, Air Force Early Warning Academy, Wu Han, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113833019","display_name":"Qinghua You","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"You Qing-hua","raw_affiliation_strings":["Unit 95980 of the Chinese People Liberation Army, Xiang Yang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Unit 95980 of the Chinese People Liberation Army, Xiang Yang, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066740984","display_name":"Ning Ma","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ma Ning","raw_affiliation_strings":["Air Force Early Warning Academy, Wu Han, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Air Force Early Warning Academy, Wu Han, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2369,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.56833307,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9997000098228455,"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":0.9997000098228455,"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/T10891","display_name":"Radar Systems and Signal Processing","score":0.9973999857902527,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9965999722480774,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/initialization","display_name":"Initialization","score":0.8747907876968384},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.7628288865089417},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.6935394406318665},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6363142728805542},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5877028107643127},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.5440924763679504},{"id":"https://openalex.org/keywords/matching-pursuit","display_name":"Matching pursuit","score":0.5052102208137512},{"id":"https://openalex.org/keywords/krylov-subspace","display_name":"Krylov subspace","score":0.4275316298007965},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38846781849861145},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3012040853500366},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.24762442708015442},{"id":"https://openalex.org/keywords/iterative-method","display_name":"Iterative method","score":0.14614182710647583}],"concepts":[{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.8747907876968384},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.7628288865089417},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6935394406318665},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6363142728805542},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5877028107643127},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.5440924763679504},{"id":"https://openalex.org/C156872377","wikidata":"https://www.wikidata.org/wiki/Q6786281","display_name":"Matching pursuit","level":3,"score":0.5052102208137512},{"id":"https://openalex.org/C147060835","wikidata":"https://www.wikidata.org/wiki/Q1757151","display_name":"Krylov subspace","level":3,"score":0.4275316298007965},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38846781849861145},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3012040853500366},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.24762442708015442},{"id":"https://openalex.org/C159694833","wikidata":"https://www.wikidata.org/wiki/Q2321565","display_name":"Iterative method","level":2,"score":0.14614182710647583},{"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/icspcc.2017.8242422","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icspcc.2017.8242422","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC)","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":15,"referenced_works":["https://openalex.org/W1587025821","https://openalex.org/W1770500012","https://openalex.org/W1976683157","https://openalex.org/W2044762091","https://openalex.org/W2091256848","https://openalex.org/W2098521117","https://openalex.org/W2106407813","https://openalex.org/W2115144080","https://openalex.org/W2151002494","https://openalex.org/W2160979406","https://openalex.org/W2296616510","https://openalex.org/W2963702538","https://openalex.org/W4250955649","https://openalex.org/W6673172288","https://openalex.org/W6682418452"],"related_works":["https://openalex.org/W2042644197","https://openalex.org/W2073241848","https://openalex.org/W3204184292","https://openalex.org/W2785927776","https://openalex.org/W3176564347","https://openalex.org/W2020549994","https://openalex.org/W4220674950","https://openalex.org/W2323113259","https://openalex.org/W4283773090","https://openalex.org/W419730749"],"abstract_inverted_index":{"In":[0,75],"order":[1],"to":[2,97,101],"make":[3],"full":[4],"use":[5],"of":[6,11,42,51,57,61,73,79,86,90,124,128,138,150],"the":[7,22,35,43,48,52,55,58,70,76,80,94,98,102,107,119,126,131,136,139,148,151],"joint":[8],"sparse":[9,12],"characteristics":[10],"signals,":[13],"a":[14],"new":[15],"distributed":[16,112],"Subspace":[17,23],"Pursuit":[18,24],"algorithm":[19,26,33,110],"based":[20,115],"on":[21,116],"(SP)":[25],"is":[27,122],"proposed":[28,120,152],"in":[29],"this":[30],"paper.":[31],"The":[32],"improves":[34],"support":[36,53,81,103],"set":[37,72],"initialization":[38,49],"and":[39,92,111,134,144],"update":[40,77],"processing":[41],"traditional":[44],"SP":[45,109,117],"algorithm.":[46],"During":[47],"stage":[50,78],"set,":[54,82],"positions":[56,95],"larger":[59,99],"values":[60,85,100,133],"inner":[62],"product":[63],"appear":[64],"most":[65],"times":[66],"were":[67],"chosen":[68],"as":[69],"initial":[71],"support.":[74],"sum":[83],"coefficient":[84],"all":[87],"non-zero":[88],"entries":[89],"signals":[91],"add":[93],"corresponding":[96],"set.":[104],"Compared":[105],"with":[106],"existing":[108],"algorithms":[113],"which":[114],"algorithm,":[118],"method":[121],"capable":[123],"improving":[125],"accuracy":[127],"reconstruction,":[129],"reducing":[130],"measured":[132],"boosting":[135],"efficiency":[137],"signal":[140],"reconstruction.":[141],"Theoretical":[142],"analysis":[143],"simulation":[145],"results":[146],"show":[147],"effectiveness":[149],"method.":[153]},"counts_by_year":[{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}