{"id":"https://openalex.org/W3005033407","doi":"https://doi.org/10.1109/lcomm.2020.2971216","title":"Detection of Frequency-Hopping Signals With Deep Learning","display_name":"Detection of Frequency-Hopping Signals With Deep Learning","publication_year":2020,"publication_date":"2020-02-03","ids":{"openalex":"https://openalex.org/W3005033407","doi":"https://doi.org/10.1109/lcomm.2020.2971216","mag":"3005033407"},"language":"en","primary_location":{"id":"doi:10.1109/lcomm.2020.2971216","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lcomm.2020.2971216","pdf_url":null,"source":{"id":"https://openalex.org/S147316732","display_name":"IEEE Communications Letters","issn_l":"1089-7798","issn":["1089-7798","1558-2558","2373-7891"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310316002","host_organization_name":"IEEE Communications Society","host_organization_lineage":["https://openalex.org/P4310316002","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Communications Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Communications Letters","raw_type":"journal-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/A5067216331","display_name":"Kyung-Gyu Lee","orcid":"https://orcid.org/0000-0001-9917-9845"},"institutions":[{"id":"https://openalex.org/I197347611","display_name":"Korea University","ror":"https://ror.org/047dqcg40","country_code":"KR","type":"education","lineage":["https://openalex.org/I197347611"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Kyung-Gyu Lee","raw_affiliation_strings":["Korea University, Seoul, South Korea"],"affiliations":[{"raw_affiliation_string":"Korea University, Seoul, South Korea","institution_ids":["https://openalex.org/I197347611"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016237867","display_name":"Seong\u2010Jun Oh","orcid":"https://orcid.org/0000-0002-0235-9987"},"institutions":[{"id":"https://openalex.org/I197347611","display_name":"Korea University","ror":"https://ror.org/047dqcg40","country_code":"KR","type":"education","lineage":["https://openalex.org/I197347611"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Seong-Jun Oh","raw_affiliation_strings":["Graduate School of Information Security, Korea University, Seoul, South Korea"],"affiliations":[{"raw_affiliation_string":"Graduate School of Information Security, Korea University, Seoul, South Korea","institution_ids":["https://openalex.org/I197347611"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5067216331"],"corresponding_institution_ids":["https://openalex.org/I197347611"],"apc_list":null,"apc_paid":null,"fwci":3.3518,"has_fulltext":false,"cited_by_count":36,"citation_normalized_percentile":{"value":0.92939406,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"24","issue":"5","first_page":"1042","last_page":"1046"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9984999895095825,"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"}},"topics":[{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9984999895095825,"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/T12131","display_name":"Wireless Signal Modulation Classification","score":0.9980999827384949,"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/T11021","display_name":"ECG Monitoring and Analysis","score":0.9961000084877014,"subfield":{"id":"https://openalex.org/subfields/2705","display_name":"Cardiology and Cardiovascular Medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/spectrogram","display_name":"Spectrogram","score":0.8860337138175964},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7715210914611816},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6646602153778076},{"id":"https://openalex.org/keywords/spectral-leakage","display_name":"Spectral leakage","score":0.6053885817527771},{"id":"https://openalex.org/keywords/time\u2013frequency-analysis","display_name":"Time\u2013frequency analysis","score":0.5388194918632507},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5350939035415649},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.5249852538108826},{"id":"https://openalex.org/keywords/frequency-hopping-spread-spectrum","display_name":"Frequency-hopping spread spectrum","score":0.5162106156349182},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5129405856132507},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5004076957702637},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4817364513874054},{"id":"https://openalex.org/keywords/leakage","display_name":"Leakage (economics)","score":0.41590258479118347},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.39179515838623047},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.2964931130409241},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.2049759030342102}],"concepts":[{"id":"https://openalex.org/C45273575","wikidata":"https://www.wikidata.org/wiki/Q578970","display_name":"Spectrogram","level":2,"score":0.8860337138175964},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7715210914611816},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6646602153778076},{"id":"https://openalex.org/C113407356","wikidata":"https://www.wikidata.org/wiki/Q1431214","display_name":"Spectral leakage","level":3,"score":0.6053885817527771},{"id":"https://openalex.org/C142433447","wikidata":"https://www.wikidata.org/wiki/Q7806653","display_name":"Time\u2013frequency analysis","level":3,"score":0.5388194918632507},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5350939035415649},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.5249852538108826},{"id":"https://openalex.org/C122962297","wikidata":"https://www.wikidata.org/wiki/Q1136013","display_name":"Frequency-hopping spread spectrum","level":2,"score":0.5162106156349182},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5129405856132507},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5004076957702637},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4817364513874054},{"id":"https://openalex.org/C2777042071","wikidata":"https://www.wikidata.org/wiki/Q6509304","display_name":"Leakage (economics)","level":2,"score":0.41590258479118347},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.39179515838623047},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2964931130409241},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.2049759030342102},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.0},{"id":"https://openalex.org/C75172450","wikidata":"https://www.wikidata.org/wiki/Q623950","display_name":"Fast Fourier transform","level":2,"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C139719470","wikidata":"https://www.wikidata.org/wiki/Q39680","display_name":"Macroeconomics","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lcomm.2020.2971216","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lcomm.2020.2971216","pdf_url":null,"source":{"id":"https://openalex.org/S147316732","display_name":"IEEE Communications Letters","issn_l":"1089-7798","issn":["1089-7798","1558-2558","2373-7891"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310316002","host_organization_name":"IEEE Communications Society","host_organization_lineage":["https://openalex.org/P4310316002","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Communications Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Communications Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Partnerships for the goals","score":0.4099999964237213,"id":"https://metadata.un.org/sdg/17"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320334874","display_name":"Defense Acquisition Program Administration","ror":"https://ror.org/04bjg9m96"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1677182931","https://openalex.org/W1686810756","https://openalex.org/W1998978351","https://openalex.org/W2061046832","https://openalex.org/W2065424480","https://openalex.org/W2336509392","https://openalex.org/W2511736952","https://openalex.org/W2546875627","https://openalex.org/W2809619574","https://openalex.org/W2897920400","https://openalex.org/W2898716605","https://openalex.org/W2907930484","https://openalex.org/W2944313727","https://openalex.org/W2962835968","https://openalex.org/W6637373629"],"related_works":["https://openalex.org/W1889291648","https://openalex.org/W2533590149","https://openalex.org/W335396218","https://openalex.org/W1504214173","https://openalex.org/W1600447354","https://openalex.org/W1589126043","https://openalex.org/W200102888","https://openalex.org/W2035480840","https://openalex.org/W2602361891","https://openalex.org/W2107964963"],"abstract_inverted_index":{"Detection":[0],"of":[1,77],"the":[2,9,27,66,83,91],"frequency-hopping":[3],"(FH)":[4],"signal":[5],"is":[6,12,24,87],"challenging":[7],"when":[8],"hopping":[10],"rate":[11],"unknown.":[13],"Conventional":[14],"spectrogram-based":[15],"schemes":[16],"can":[17],"detect":[18],"FH":[19],"signals,":[20],"but":[21],"its":[22],"performance":[23],"limited":[25],"by":[26,57,70],"time-frequency":[28,67],"resolution":[29,68],"trade-off":[30,69],"and":[31,44,93],"spectral":[32,55],"leakage.":[33],"To":[34],"alleviate":[35],"this":[36],"issue,":[37],"we":[38],"design":[39],"convolutional":[40],"neural":[41,47],"network":[42,48],"(CNN)":[43],"hybrid":[45,62,84],"CNN/recurrent":[46],"(RNN)-based":[49],"schemes.":[50,96],"The":[51,61],"CNN-based":[52,92],"scheme":[53,64,86],"alleviates":[54],"leakage":[56],"using":[58,71],"feature":[59,72],"maps.":[60],"CNN/RNN-based":[63,85],"mitigates":[65],"maps":[73],"extracted":[74],"from":[75],"spectrograms":[76],"various":[78],"window":[79],"lengths.":[80],"In":[81],"simulations,":[82],"shown":[88],"to":[89],"outperform":[90],"conventional":[94],"detection":[95]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":11},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":5}],"updated_date":"2026-03-28T08:17:26.163206","created_date":"2025-10-10T00:00:00"}