{"id":"https://openalex.org/W2783045968","doi":"https://doi.org/10.1109/icsai.2017.8248442","title":"A hybrid method for classification and identification of emitter signals","display_name":"A hybrid method for classification and identification of emitter signals","publication_year":2017,"publication_date":"2017-11-01","ids":{"openalex":"https://openalex.org/W2783045968","doi":"https://doi.org/10.1109/icsai.2017.8248442","mag":"2783045968"},"language":"en","primary_location":{"id":"doi:10.1109/icsai.2017.8248442","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icsai.2017.8248442","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 4th International Conference on Systems and Informatics (ICSAI)","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/A5100441230","display_name":"Xiaonan Zhang","orcid":"https://orcid.org/0000-0001-8531-8664"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiaonan Zhang","raw_affiliation_strings":["College of Systems Engineering, National University of Defense Technology, Changsha, P. R. China"],"affiliations":[{"raw_affiliation_string":"College of Systems Engineering, National University of Defense Technology, Changsha, P. R. China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100752688","display_name":"Pengcheng Luo","orcid":"https://orcid.org/0000-0003-0586-3078"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pengcheng Luo","raw_affiliation_strings":["College of Systems Engineering, National University of Defense Technology, Changsha, P. R. China"],"affiliations":[{"raw_affiliation_string":"College of Systems Engineering, National University of Defense Technology, Changsha, P. R. China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056674151","display_name":"Xinwu Hu","orcid":"https://orcid.org/0000-0003-3032-7250"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinwu Hu","raw_affiliation_strings":["College of Systems Engineering, National University of Defense Technology, Changsha, P. R. China"],"affiliations":[{"raw_affiliation_string":"College of Systems Engineering, National University of Defense Technology, Changsha, P. R. China","institution_ids":["https://openalex.org/I170215575"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100441230"],"corresponding_institution_ids":["https://openalex.org/I170215575"],"apc_list":null,"apc_paid":null,"fwci":0.5851,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.77014492,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":"46","issue":null,"first_page":"1060","last_page":"1065"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9901999831199646,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9901999831199646,"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/T10320","display_name":"Neural Networks and Applications","score":0.9879000186920166,"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9747999906539917,"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/cluster-analysis","display_name":"Cluster analysis","score":0.7743096351623535},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6748735904693604},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6444576382637024},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.6362718939781189},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6241646409034729},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5768539309501648},{"id":"https://openalex.org/keywords/common-emitter","display_name":"Common emitter","score":0.5749066472053528},{"id":"https://openalex.org/keywords/electronic-warfare","display_name":"Electronic warfare","score":0.5283181071281433},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5091952681541443},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5002663135528564},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.4863346219062805},{"id":"https://openalex.org/keywords/jamming","display_name":"Jamming","score":0.4502255320549011},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.44411975145339966},{"id":"https://openalex.org/keywords/hierarchical-clustering","display_name":"Hierarchical clustering","score":0.44138070940971375},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.21919789910316467},{"id":"https://openalex.org/keywords/electronic-engineering","display_name":"Electronic engineering","score":0.17227068543434143},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.08931604027748108}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7743096351623535},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6748735904693604},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6444576382637024},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.6362718939781189},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6241646409034729},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5768539309501648},{"id":"https://openalex.org/C46918542","wikidata":"https://www.wikidata.org/wiki/Q1648344","display_name":"Common emitter","level":2,"score":0.5749066472053528},{"id":"https://openalex.org/C133082901","wikidata":"https://www.wikidata.org/wiki/Q272826","display_name":"Electronic warfare","level":3,"score":0.5283181071281433},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5091952681541443},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5002663135528564},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.4863346219062805},{"id":"https://openalex.org/C2779079576","wikidata":"https://www.wikidata.org/wiki/Q17092823","display_name":"Jamming","level":2,"score":0.4502255320549011},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.44411975145339966},{"id":"https://openalex.org/C92835128","wikidata":"https://www.wikidata.org/wiki/Q1277447","display_name":"Hierarchical clustering","level":3,"score":0.44138070940971375},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.21919789910316467},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.17227068543434143},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.08931604027748108},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.0},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/icsai.2017.8248442","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icsai.2017.8248442","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 4th International Conference on Systems and Informatics (ICSAI)","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":33,"referenced_works":["https://openalex.org/W1494289067","https://openalex.org/W1561568150","https://openalex.org/W1709057194","https://openalex.org/W1970874350","https://openalex.org/W1985157189","https://openalex.org/W1997908190","https://openalex.org/W1998960312","https://openalex.org/W2010657328","https://openalex.org/W2017431647","https://openalex.org/W2024034573","https://openalex.org/W2052812103","https://openalex.org/W2056147747","https://openalex.org/W2060473300","https://openalex.org/W2069890526","https://openalex.org/W2078231942","https://openalex.org/W2088322911","https://openalex.org/W2091825929","https://openalex.org/W2103753221","https://openalex.org/W2108286220","https://openalex.org/W2114653151","https://openalex.org/W2116413397","https://openalex.org/W2124077530","https://openalex.org/W2125993116","https://openalex.org/W2135004991","https://openalex.org/W2142772712","https://openalex.org/W2142885311","https://openalex.org/W2149280070","https://openalex.org/W2149327284","https://openalex.org/W2153718237","https://openalex.org/W2161835057","https://openalex.org/W2166280719","https://openalex.org/W2567135925","https://openalex.org/W6681183030"],"related_works":["https://openalex.org/W2350990509","https://openalex.org/W2391130903","https://openalex.org/W2110612166","https://openalex.org/W3081127448","https://openalex.org/W3088345466","https://openalex.org/W3036103644","https://openalex.org/W2355624950","https://openalex.org/W2354671671","https://openalex.org/W2034832342","https://openalex.org/W2363623945"],"abstract_inverted_index":{"Communication":[0],"emitter":[1,17,40],"identification":[2,38],"has":[3],"been":[4],"recognized":[5],"as":[6],"an":[7],"indispensable":[8],"task":[9],"for":[10],"electronic":[11,29],"intelligence":[12],"system.":[13],"Recognition":[14],"of":[15,21,39,57,79,86],"communication":[16],"signals":[18,123],"is":[19,73,108,117,141,149],"presupposition":[20],"jamming":[22],"or":[23],"striking":[24],"enemies'":[25],"equipment":[26],"effectively":[27],"in":[28,92],"warfare.":[30],"This":[31],"paper":[32],"mainly":[33],"studies":[34],"the":[35,43,54,84,115,138,146],"classification":[36,98],"and":[37,70,105,114,143,145],"signals.":[41],"Firstly,":[42],"eigenvectors":[44],"are":[45,124],"reduced":[46],"by":[47,126],"principal":[48],"component":[49],"analysis":[50],"(PCA)":[51],"to":[52,75,89,110,128,151],"realize":[53],"feature":[55],"extraction":[56],"signal":[58,80,93],"samples.":[59],"On":[60],"this":[61],"basis,":[62],"a":[63,96],"flexible":[64],"clustering":[65,69,72,131,139],"model,":[66],"integrating":[67],"K-means":[68],"hierarchical":[71],"proposed":[74],"distinguish":[76],"different":[77],"types":[78],"samples,":[81],"which":[82],"overcomes":[83],"disadvantage":[85],"inaccuracy":[87],"due":[88],"single":[90],"algorithm":[91],"classification.":[94],"Then":[95],"hybrid":[97],"model":[99,140],"with":[100],"k-nearest":[101],"neighbors,":[102],"random":[103],"forest":[104],"neural":[106],"network":[107],"constructed":[109],"identify":[111],"individual":[112],"signals,":[113],"accuracy":[116,148],"higher":[118],"than":[119],"97%.":[120],"Finally,":[121],"artificial":[122],"generated":[125],"MATLAB":[127],"test":[129],"our":[130],"model.":[132],"The":[133],"experimental":[134],"results":[135],"show":[136],"that":[137],"efficient":[142],"reliable,":[144],"average":[147],"up":[150],"93.4%.":[152]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}