{"id":"https://openalex.org/W2963823349","doi":"https://doi.org/10.25080/majora-7ddc1dd1-002","title":"Expert RF Feature Extraction to Win the Army RCO AI Signal Classification Challenge","display_name":"Expert RF Feature Extraction to Win the Army RCO AI Signal Classification Challenge","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2963823349","doi":"https://doi.org/10.25080/majora-7ddc1dd1-002","mag":"2963823349"},"language":"en","primary_location":{"id":"doi:10.25080/majora-7ddc1dd1-002","is_oa":true,"landing_page_url":"https://doi.org/10.25080/majora-7ddc1dd1-002","pdf_url":"http://conference.scipy.org/proceedings/scipy2019/pdfs/aero_ef_logue.pdf","source":{"id":"https://openalex.org/S4220651651","display_name":"Proceedings of the Python in Science Conferences","issn_l":"2575-9752","issn":["2575-9752"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Python in Science Conference","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"http://conference.scipy.org/proceedings/scipy2019/pdfs/aero_ef_logue.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5037807924","display_name":"Kyle Logue","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kyle Logue","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056357198","display_name":"Esteban L. Valles","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Esteban Valles","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047171478","display_name":"Andres Vila","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Andres Vila","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016843173","display_name":"Alex Utter","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Alex Utter","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005321477","display_name":"Darren Semmen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Darren Semmen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023398291","display_name":"Eugene Grayver","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Eugene Grayver","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055981010","display_name":"Sebastian Olsen","orcid":"https://orcid.org/0000-0003-4461-885X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sebastian Olsen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5057133904","display_name":"Donna Branchevsky","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Donna Branchevsky","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":8,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.0122,"has_fulltext":true,"cited_by_count":14,"citation_normalized_percentile":{"value":0.82734408,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"13","last_page":"20"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12131","display_name":"Wireless Signal Modulation Classification","score":0.9980000257492065,"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":0.9980000257492065,"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/T10662","display_name":"Ultrasonics and Acoustic Wave Propagation","score":0.958299994468689,"subfield":{"id":"https://openalex.org/subfields/2211","display_name":"Mechanics of Materials"},"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/T12447","display_name":"Spider Taxonomy and Behavior Studies","score":0.9302999973297119,"subfield":{"id":"https://openalex.org/subfields/1311","display_name":"Genetics"},"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7488245368003845},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7436726093292236},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6453650593757629},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.6053632497787476},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5798114538192749},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5582975745201111},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5439292788505554},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5290369391441345},{"id":"https://openalex.org/keywords/waveform","display_name":"Waveform","score":0.49383360147476196},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.47412538528442383},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.44235795736312866},{"id":"https://openalex.org/keywords/modulation","display_name":"Modulation (music)","score":0.4264225959777832},{"id":"https://openalex.org/keywords/kurtosis","display_name":"Kurtosis","score":0.41889768838882446},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.10929185152053833},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10113200545310974},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.08590877056121826},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.07746610045433044}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7488245368003845},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7436726093292236},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6453650593757629},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.6053632497787476},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5798114538192749},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5582975745201111},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5439292788505554},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5290369391441345},{"id":"https://openalex.org/C197424946","wikidata":"https://www.wikidata.org/wiki/Q1165717","display_name":"Waveform","level":3,"score":0.49383360147476196},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.47412538528442383},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.44235795736312866},{"id":"https://openalex.org/C123079801","wikidata":"https://www.wikidata.org/wiki/Q750240","display_name":"Modulation (music)","level":2,"score":0.4264225959777832},{"id":"https://openalex.org/C166963901","wikidata":"https://www.wikidata.org/wiki/Q287251","display_name":"Kurtosis","level":2,"score":0.41889768838882446},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.10929185152053833},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10113200545310974},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.08590877056121826},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.07746610045433044},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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/C107038049","wikidata":"https://www.wikidata.org/wiki/Q35986","display_name":"Aesthetics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.25080/majora-7ddc1dd1-002","is_oa":true,"landing_page_url":"https://doi.org/10.25080/majora-7ddc1dd1-002","pdf_url":"http://conference.scipy.org/proceedings/scipy2019/pdfs/aero_ef_logue.pdf","source":{"id":"https://openalex.org/S4220651651","display_name":"Proceedings of the Python in Science Conferences","issn_l":"2575-9752","issn":["2575-9752"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Python in Science Conference","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.25080/majora-7ddc1dd1-002","is_oa":true,"landing_page_url":"https://doi.org/10.25080/majora-7ddc1dd1-002","pdf_url":"http://conference.scipy.org/proceedings/scipy2019/pdfs/aero_ef_logue.pdf","source":{"id":"https://openalex.org/S4220651651","display_name":"Proceedings of the Python in Science Conferences","issn_l":"2575-9752","issn":["2575-9752"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Python in Science Conference","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2963823349.pdf","grobid_xml":"https://content.openalex.org/works/W2963823349.grobid-xml"},"referenced_works_count":17,"referenced_works":["https://openalex.org/W1580469463","https://openalex.org/W1986510668","https://openalex.org/W1992688426","https://openalex.org/W2014282978","https://openalex.org/W2056132907","https://openalex.org/W2114299240","https://openalex.org/W2130014182","https://openalex.org/W2143426320","https://openalex.org/W2145614561","https://openalex.org/W2151223056","https://openalex.org/W2170211487","https://openalex.org/W2243397390","https://openalex.org/W2618376619","https://openalex.org/W2773170971","https://openalex.org/W2774644650","https://openalex.org/W4248573116","https://openalex.org/W6821000344"],"related_works":["https://openalex.org/W4381516319","https://openalex.org/W1506384729","https://openalex.org/W2037499216","https://openalex.org/W4225568567","https://openalex.org/W4286378979","https://openalex.org/W2075698830","https://openalex.org/W3127045225","https://openalex.org/W3216026256","https://openalex.org/W2059891554","https://openalex.org/W4235233670"],"abstract_inverted_index":{"Automatic":[0],"modulation":[1,212],"classification":[2,71,120],"is":[3,35,66,72,85],"a":[4,73,132,187],"challenging":[5],"problem":[6,24],"with":[7,186,219,232,242],"multiple":[8],"applications":[9],"including":[10],"cognitive":[11],"radio":[12],"and":[13,52,126,142,168,193,206,236],"signals":[14,237],"intelligence.":[15],"Most":[16],"of":[17,40,76,190,203,224],"the":[18,29,41,89,94,148,181],"existing":[19],"efforts":[20],"to":[21,31,57,69,87,146],"solve":[22],"this":[23,58,77,107],"are":[25,43,129,222],"only":[26],"applicable":[27],"when":[28,217],"signal":[30,42,64,104,112,119,191],"noise":[32],"ratio":[33],"(SNR)":[34],"high":[36],"and/or":[37],"long":[38],"observations":[39],"available.":[44],"Recent":[45],"work":[46],"has":[47],"focused":[48],"on":[49,102],"applying":[50],"shallow":[51,143],"deep":[53,90,124,220],"machine":[54],"learning":[55,91,125,221],"(ML)":[56],"problem.":[59],"Feature":[60],"generation,":[61],"where":[62],"raw":[63],"information":[65],"transformed":[67],"prior":[68],"attempting":[70],"key":[74],"part":[75],"process.":[78],"A":[79],"big":[80],"question":[81],"that":[82],"researchers":[83],"face":[84],"whether":[86],"let":[88],"system":[92],"infer":[93],"relevant":[95],"features":[96,100,136,159,192,205],"or":[97],"build":[98],"expert":[99],"based":[101],"expected":[103],"characteristics.":[105],"In":[106],"paper,":[108],"we":[109],"present":[110],"novel":[111],"feature":[113,196],"extraction":[114],"methods":[115,215],"for":[116,175],"use":[117],"in":[118,131,209],"via":[121,139],"ML.":[122],"The":[123,158,214],"combined":[127,218],"approaches":[128],"discussed":[130,216],"simultaneous":[133],"publication.":[134],"Expert":[135],"were":[137],"utilized":[138],"ensemble":[140],"leaning":[141],"neural":[144],"networks":[145],"win":[147],"Army":[149,248],"Rapid":[150],"Capability":[151],"Office":[152],"(RCO)":[153],"2018":[154],"Signal":[155],"Classification":[156],"Challenge.":[157],"include":[160],"both":[161],"standard":[162],"statistical":[163,183],"measurements":[164,173],"such":[165],"as":[166,170,172],"variance":[167],"kurtosis,":[169],"well":[171],"tailored":[174],"specific":[176],"waveform":[177],"families.":[178],"We":[179,198],"discuss":[180,194,207],"best":[182],"descriptors":[184],"along":[185],"ranked":[188],"list":[189],"individual":[195],"importance.":[197],"then":[199],"demonstrate":[200],"our":[201],"implementation":[202],"these":[204],"effectiveness":[208],"estimating":[210],"different":[211],"classes.":[213],"capable":[223],"correctly":[225],"classifying":[226],"waveforms":[227],"at":[228,238],"-10":[229],"dB":[230,240],"SNR":[231,241],"over":[233,243],"63%":[234],"accuracy":[235,245],"+10":[239],"95%":[244],"from":[246],"an":[247],"RCO":[249],"provided":[250],"training":[251],"set.":[252]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":7}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}