{"id":"https://openalex.org/W2112525343","doi":"https://doi.org/10.1109/ijcnn.2008.4633860","title":"Radar emitter signal recognition based on atomic decomposition","display_name":"Radar emitter signal recognition based on atomic decomposition","publication_year":2008,"publication_date":"2008-06-01","ids":{"openalex":"https://openalex.org/W2112525343","doi":"https://doi.org/10.1109/ijcnn.2008.4633860","mag":"2112525343"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2008.4633860","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2008.4633860","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence)","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/A5101545213","display_name":"Ming Zhu","orcid":"https://orcid.org/0000-0002-3422-2328"},"institutions":[{"id":"https://openalex.org/I24201400","display_name":"Chengdu University of Information Technology","ror":"https://ror.org/01yxwrh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I24201400"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ming Zhu","raw_affiliation_strings":["Department of Control Engineering, Chengdu University of Information and Technology, Chengdu, Sichuan, China"],"affiliations":[{"raw_affiliation_string":"Department of Control Engineering, Chengdu University of Information and Technology, Chengdu, Sichuan, China","institution_ids":["https://openalex.org/I24201400"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101522872","display_name":"Weidong Jin","orcid":null},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weidong Jin","raw_affiliation_strings":["School of Electrical Engineering, Southwest Jiaotong University, Chengdu, Sichuan, China"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Southwest Jiaotong University, Chengdu, Sichuan, China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5040589456","display_name":"Laizhao Hu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Laizhao Hu","raw_affiliation_strings":["National EW Laboratory, Chengdu, Sichuan, China"],"affiliations":[{"raw_affiliation_string":"National EW Laboratory, Chengdu, Sichuan, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101545213"],"corresponding_institution_ids":["https://openalex.org/I24201400"],"apc_list":null,"apc_paid":null,"fwci":0.5721,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.78623018,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"23","issue":null,"first_page":"633","last_page":"636"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12131","display_name":"Wireless Signal Modulation Classification","score":0.9983999729156494,"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"}},"topics":[{"id":"https://openalex.org/T12131","display_name":"Wireless Signal Modulation Classification","score":0.9983999729156494,"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"}},{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9968000054359436,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9897000193595886,"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/radar","display_name":"Radar","score":0.7021929025650024},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6406338810920715},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6108212471008301},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5623262524604797},{"id":"https://openalex.org/keywords/common-emitter","display_name":"Common emitter","score":0.5357851982116699},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.5176239609718323},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5105841755867004},{"id":"https://openalex.org/keywords/matching-pursuit","display_name":"Matching pursuit","score":0.48417335748672485},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.47174322605133057},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4669327139854431},{"id":"https://openalex.org/keywords/fast-fourier-transform","display_name":"Fast Fourier transform","score":0.4267076551914215},{"id":"https://openalex.org/keywords/radar-tracker","display_name":"Radar tracker","score":0.4213467240333557},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.4211556315422058},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.41718754172325134},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.37127822637557983},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3100634217262268},{"id":"https://openalex.org/keywords/electronic-engineering","display_name":"Electronic engineering","score":0.27424144744873047},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.2178162932395935},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16675817966461182},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.08127859234809875},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.07349935173988342}],"concepts":[{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.7021929025650024},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6406338810920715},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6108212471008301},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5623262524604797},{"id":"https://openalex.org/C46918542","wikidata":"https://www.wikidata.org/wiki/Q1648344","display_name":"Common emitter","level":2,"score":0.5357851982116699},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.5176239609718323},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5105841755867004},{"id":"https://openalex.org/C156872377","wikidata":"https://www.wikidata.org/wiki/Q6786281","display_name":"Matching pursuit","level":3,"score":0.48417335748672485},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.47174322605133057},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4669327139854431},{"id":"https://openalex.org/C75172450","wikidata":"https://www.wikidata.org/wiki/Q623950","display_name":"Fast Fourier transform","level":2,"score":0.4267076551914215},{"id":"https://openalex.org/C32283439","wikidata":"https://www.wikidata.org/wiki/Q1407014","display_name":"Radar tracker","level":3,"score":0.4213467240333557},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.4211556315422058},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.41718754172325134},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.37127822637557983},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3100634217262268},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.27424144744873047},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2178162932395935},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16675817966461182},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.08127859234809875},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.07349935173988342},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","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/ijcnn.2008.4633860","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2008.4633860","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.6000000238418579}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":5,"referenced_works":["https://openalex.org/W1561568150","https://openalex.org/W2115552570","https://openalex.org/W2117761544","https://openalex.org/W2151693816","https://openalex.org/W2391735301"],"related_works":["https://openalex.org/W2042644197","https://openalex.org/W2073241848","https://openalex.org/W2785927776","https://openalex.org/W2020549994","https://openalex.org/W4220674950","https://openalex.org/W2381915087","https://openalex.org/W3130682819","https://openalex.org/W1980565639","https://openalex.org/W2790856699","https://openalex.org/W963760361"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"a":[3],"novel":[4],"approach":[5,132],"based":[6,20],"on":[7,21],"Gaussian":[8,26],"Chirplet":[9,27],"Atoms":[10],"is":[11,35,53,126,136],"presented":[12],"to":[13,37,55,73,85],"automatically":[14],"recognise":[15],"radar":[16,48,112],"emitter":[17,49,113],"signals.":[18,114],"Firstly,":[19],"the":[22,29,39,42,46,58,70,75,81,95,104,108,123,131,139],"over-completed":[23],"dictionary":[24],"of":[25,41,61,64,69,102,111,133],"atoms,":[28],"improved":[30],"matching":[31],"pursuit":[32],"(MP)":[33],"algorithm":[34],"applied":[36],"extract":[38],"features":[40],"time-frequency":[43],"atoms":[44],"from":[45],"typical":[47],"signals,":[50],"and":[51,106],"FFT":[52],"introduced":[54],"effectively":[56],"reduce":[57,67],"time":[59],"complexity":[60],"searching":[62],"step":[63],"MP.":[65],"Secondly,":[66],"dimension":[68],"feature":[71,77,97],"parameters":[72],"re-extract":[74],"classification":[76,96],"vectors.":[78],"Finally,":[79],"adopt":[80],"hierarchy":[82],"decision":[83],"strategy":[84],"realize":[86],"automatic":[87],"classification.":[88],"The":[89],"simulation":[90],"experiment":[91],"result":[92],"shows":[93],"that":[94],"vector":[98],"has":[99],"good":[100],"properties":[101],"clustering":[103],"same":[105],"separating":[107],"different":[109],"kind":[110],"Over":[115],"90%":[116],"recognition":[117,135],"accuracy":[118],"can":[119],"be":[120],"achieved":[121],"as":[122],"signal-to-noise":[124],"ratio":[125],"greater":[127],"than":[128],"-4dB.":[129],"Therefore,":[130],"signal":[134],"feasible":[137],"in":[138],"practical":[140],"engineering":[141],"area.":[142]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
