{"id":"https://openalex.org/W1981994374","doi":"https://doi.org/10.1109/wcsp.2013.6677192","title":"Comprehensive evaluation of cumulant-based and Kolmogorov-Smirnov-based modulation classifiers","display_name":"Comprehensive evaluation of cumulant-based and Kolmogorov-Smirnov-based modulation classifiers","publication_year":2013,"publication_date":"2013-10-01","ids":{"openalex":"https://openalex.org/W1981994374","doi":"https://doi.org/10.1109/wcsp.2013.6677192","mag":"1981994374"},"language":"en","primary_location":{"id":"doi:10.1109/wcsp.2013.6677192","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wcsp.2013.6677192","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 International Conference on Wireless Communications and Signal Processing","raw_type":"proceedings-article"},"type":"conference-paper","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/A5101935050","display_name":"Jingwen Zhang","orcid":"https://orcid.org/0000-0001-8698-2452"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingwen Zhang","raw_affiliation_strings":["School of Electronics and Information Engineering, Beijing Jiaotong University, Beijing, China","Sch. of Electron. & Inf. Eng., Beijing Jiaotong Univ., Beijing, , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronics and Information Engineering, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]},{"raw_affiliation_string":"Sch. of Electron. & Inf. Eng., Beijing Jiaotong Univ., Beijing, , China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102985769","display_name":"Fanggang Wang","orcid":"https://orcid.org/0000-0002-2014-7611"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fanggang Wang","raw_affiliation_strings":["State Key Lab of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing, China","State Key Lab of Rail Traffic Control & Safety, Beijing Jiaotong University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Lab of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]},{"raw_affiliation_string":"State Key Lab of Rail Traffic Control & Safety, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100307663","display_name":"Zhong Zhangdui","orcid":null},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhangdui Zhong","raw_affiliation_strings":["State Key Lab of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing, China","State Key Lab of Rail Traffic Control & Safety, Beijing Jiaotong University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Lab of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]},{"raw_affiliation_string":"State Key Lab of Rail Traffic Control & Safety, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I21193070"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"77","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12131","display_name":"Wireless Signal Modulation Classification","score":0.9997000098228455,"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":0.9997000098228455,"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/T12946","display_name":"Fractal and DNA sequence analysis","score":0.9848999977111816,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10891","display_name":"Radar Systems and Signal Processing","score":0.949999988079071,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/modulation","display_name":"Modulation (music)","score":0.7092901468276978},{"id":"https://openalex.org/keywords/kolmogorov\u2013smirnov-test","display_name":"Kolmogorov\u2013Smirnov test","score":0.7018040418624878},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5706732273101807},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5214145183563232},{"id":"https://openalex.org/keywords/cumulant","display_name":"Cumulant","score":0.5148676633834839},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48302969336509705},{"id":"https://openalex.org/keywords/empirical-distribution-function","display_name":"Empirical distribution function","score":0.44228595495224},{"id":"https://openalex.org/keywords/probability-distribution","display_name":"Probability distribution","score":0.43472564220428467},{"id":"https://openalex.org/keywords/statistical-hypothesis-testing","display_name":"Statistical hypothesis testing","score":0.3972419798374176},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3696269989013672},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3606860637664795},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.35446056723594666},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.06198936700820923}],"concepts":[{"id":"https://openalex.org/C123079801","wikidata":"https://www.wikidata.org/wiki/Q750240","display_name":"Modulation (music)","level":2,"score":0.7092901468276978},{"id":"https://openalex.org/C82581908","wikidata":"https://www.wikidata.org/wiki/Q575766","display_name":"Kolmogorov\u2013Smirnov test","level":3,"score":0.7018040418624878},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5706732273101807},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5214145183563232},{"id":"https://openalex.org/C172686274","wikidata":"https://www.wikidata.org/wiki/Q746007","display_name":"Cumulant","level":2,"score":0.5148676633834839},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48302969336509705},{"id":"https://openalex.org/C98385598","wikidata":"https://www.wikidata.org/wiki/Q1339385","display_name":"Empirical distribution function","level":2,"score":0.44228595495224},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.43472564220428467},{"id":"https://openalex.org/C87007009","wikidata":"https://www.wikidata.org/wiki/Q210832","display_name":"Statistical hypothesis testing","level":2,"score":0.3972419798374176},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3696269989013672},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3606860637664795},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.35446056723594666},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.06198936700820923},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/wcsp.2013.6677192","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wcsp.2013.6677192","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 International Conference on Wireless Communications and Signal Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1520508279","https://openalex.org/W1994948399","https://openalex.org/W2005956500","https://openalex.org/W2103192447","https://openalex.org/W2125175435","https://openalex.org/W2125242600","https://openalex.org/W2137240886","https://openalex.org/W2138280825","https://openalex.org/W2142363115","https://openalex.org/W2147735901","https://openalex.org/W2147893740","https://openalex.org/W2147987647","https://openalex.org/W2166509710","https://openalex.org/W2170778725","https://openalex.org/W2541868281","https://openalex.org/W3015238844","https://openalex.org/W4255375128","https://openalex.org/W6681773882"],"related_works":["https://openalex.org/W1536719639","https://openalex.org/W1588771202","https://openalex.org/W1523686749","https://openalex.org/W249541249","https://openalex.org/W2912025066","https://openalex.org/W2166481425","https://openalex.org/W2035003022","https://openalex.org/W1966024949","https://openalex.org/W2050297329","https://openalex.org/W2943190685"],"abstract_inverted_index":{"Kolmogorov-Smirnov":[0],"(K-S)":[1],"test":[2],"is":[3],"a":[4,34],"simple":[5],"and":[6,30],"robust":[7],"method":[8],"to":[9,43,46],"distinguish":[10,47],"distribution,":[11],"which":[12],"makes":[13],"the":[14,19,22,26,31,57,61,74,79],"final":[15],"decixsion":[16],"by":[17],"comparing":[18],"differences":[20],"between":[21],"empirical":[23],"cdf":[24,32],"of":[25,28,33,60],"samples":[27],"interest":[29],"hypothesized":[35],"distribution.":[36],"K-S-based":[37],"modulation":[38,50,92],"classifiers":[39,63,81],"can":[40,82],"be":[41],"applied":[42],"different":[44,66],"channels":[45],"multiple":[48],"candidate":[49],"formats.":[51,93],"In":[52],"this":[53],"paper,":[54],"we":[55],"evaluate":[56],"classification":[58,85],"probability":[59],"K-S":[62,80],"comprehensively":[64],"in":[65],"scenarios.":[67],"Extensive":[68],"simulation":[69],"results":[70],"that":[71,78],"compared":[72],"with":[73],"cumulant-based":[75],"methods":[76],"show":[77],"achieve":[83],"better":[84],"performance,":[86],"especially":[87],"when":[88],"distinguishing":[89],"higher":[90],"order":[91]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}