{"id":"https://openalex.org/W4391147927","doi":"https://doi.org/10.1109/tnnls.2024.3350609","title":"Learning Cross-Domain Features With Dual-Path Signal Transformer","display_name":"Learning Cross-Domain Features With Dual-Path Signal Transformer","publication_year":2024,"publication_date":"2024-01-23","ids":{"openalex":"https://openalex.org/W4391147927","doi":"https://doi.org/10.1109/tnnls.2024.3350609","pmid":"https://pubmed.ncbi.nlm.nih.gov/38261503"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2024.3350609","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2024.3350609","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5093772347","display_name":"Lei Zhai","orcid":"https://orcid.org/0000-0002-4935-6951"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Lei Zhai","raw_affiliation_strings":["School of Artificial Intelligence, Xidian University, Xi&#x2019;an, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Xidian University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100413875","display_name":"Yitong Li","orcid":"https://orcid.org/0000-0002-6753-6227"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yitong Li","raw_affiliation_strings":["School of Artificial Intelligence, Xidian University, Xi&#x2019;an, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Xidian University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053487344","display_name":"Zhixi Feng","orcid":"https://orcid.org/0000-0002-7372-9180"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhixi Feng","raw_affiliation_strings":["School of Artificial Intelligence, Xidian University, Xi&#x2019;an, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Xidian University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100764373","display_name":"Shuyuan Yang","orcid":"https://orcid.org/0000-0002-4796-5737"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuyuan Yang","raw_affiliation_strings":["School of Artificial Intelligence, Xidian University, Xi&#x2019;an, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Xidian University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049514215","display_name":"Hao Tan","orcid":"https://orcid.org/0000-0003-4013-417X"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Tan","raw_affiliation_strings":["School of Artificial Intelligence, Xidian University, Xi&#x2019;an, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Xidian University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5093772347"],"corresponding_institution_ids":["https://openalex.org/I149594827"],"apc_list":null,"apc_paid":null,"fwci":3.2635,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.92415183,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"36","issue":"2","first_page":"3863","last_page":"3869"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12131","display_name":"Wireless Signal Modulation Classification","score":1.0,"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":1.0,"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/T10891","display_name":"Radar Systems and Signal Processing","score":0.9483000040054321,"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/computer-science","display_name":"Computer science","score":0.6663116812705994},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.6190811395645142},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5314896106719971},{"id":"https://openalex.org/keywords/fuse","display_name":"Fuse (electrical)","score":0.5192039608955383},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.501882791519165},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.44893819093704224},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.44768595695495605},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.44566383957862854},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.43905577063560486},{"id":"https://openalex.org/keywords/time-domain","display_name":"Time domain","score":0.43449458479881287},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3300786018371582},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.135696142911911},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.12709209322929382},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.0898301899433136},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07194700837135315},{"id":"https://openalex.org/keywords/voltage","display_name":"Voltage","score":0.06982114911079407}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6663116812705994},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.6190811395645142},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5314896106719971},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.5192039608955383},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.501882791519165},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.44893819093704224},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.44768595695495605},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.44566383957862854},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.43905577063560486},{"id":"https://openalex.org/C103824480","wikidata":"https://www.wikidata.org/wiki/Q185889","display_name":"Time domain","level":2,"score":0.43449458479881287},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3300786018371582},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.135696142911911},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.12709209322929382},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0898301899433136},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07194700837135315},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.06982114911079407},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2024.3350609","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2024.3350609","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:38261503","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/38261503","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1560732540","display_name":null,"funder_award_id":"62276205","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5111323382","display_name":null,"funder_award_id":"61906145","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5498747354","display_name":null,"funder_award_id":"U22B2018","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6986719856","display_name":null,"funder_award_id":"62171357","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W2008056655","https://openalex.org/W2106186328","https://openalex.org/W2114253536","https://openalex.org/W2134069026","https://openalex.org/W2166911748","https://openalex.org/W2172189177","https://openalex.org/W2187089797","https://openalex.org/W2194775991","https://openalex.org/W2420110223","https://openalex.org/W2603396821","https://openalex.org/W2741230443","https://openalex.org/W2773170971","https://openalex.org/W2775383661","https://openalex.org/W2792764867","https://openalex.org/W2884089434","https://openalex.org/W2896457183","https://openalex.org/W2945473916","https://openalex.org/W2993484807","https://openalex.org/W3000943722","https://openalex.org/W3012311943","https://openalex.org/W3013576231","https://openalex.org/W3016118099","https://openalex.org/W3039263585","https://openalex.org/W3075060036","https://openalex.org/W3085631338","https://openalex.org/W3104028856","https://openalex.org/W3159778524","https://openalex.org/W3163383976","https://openalex.org/W3168231499","https://openalex.org/W3195600610","https://openalex.org/W3200430820","https://openalex.org/W3203455242","https://openalex.org/W4205182328","https://openalex.org/W4206998227","https://openalex.org/W4213019189","https://openalex.org/W4225725965","https://openalex.org/W4226011009","https://openalex.org/W4285108271","https://openalex.org/W4285507497","https://openalex.org/W4286212078","https://openalex.org/W4293195393","https://openalex.org/W6749825310","https://openalex.org/W6755207826","https://openalex.org/W6795062860","https://openalex.org/W6796149595","https://openalex.org/W6917408469"],"related_works":["https://openalex.org/W2595172197","https://openalex.org/W2084856301","https://openalex.org/W2127970246","https://openalex.org/W2885125400","https://openalex.org/W1989889224","https://openalex.org/W3000097931","https://openalex.org/W4382618745","https://openalex.org/W1973775000","https://openalex.org/W2354322770","https://openalex.org/W2748922771"],"abstract_inverted_index":{"The":[0],"past":[1],"decade":[2],"has":[3],"witnessed":[4],"the":[5,21,62,100,125],"rapid":[6],"development":[7],"of":[8,20,68,127],"deep":[9],"neural":[10],"networks":[11],"(DNNs)":[12],"for":[13,58,109],"automatic":[14],"modulation":[15,111],"classification":[16],"(AMC).":[17],"However,":[18],"most":[19],"available":[22],"works":[23],"learn":[24],"signal":[25,53,73,83],"features":[26,84],"from":[27],"only":[28],"a":[29,50,72],"single":[30],"domain":[31],"via":[32],"DNNs,":[33],"which":[34],"is":[35,56],"not":[36],"reliable":[37],"enough":[38],"to":[39,60,116],"work":[40],"in":[41,88,130],"uncertain":[42],"and":[43,81,97,99],"complex":[44],"electromagnetic":[45],"environments.":[46],"In":[47],"this":[48],"brief,":[49],"new":[51],"cross-domain":[52],"transformer":[54],"(CDSiT)":[55],"proposed":[57],"AMC,":[59],"explore":[61],"latent":[63],"association":[64],"between":[65],"different":[66,89],"domains":[67],"signals.":[69],"By":[70],"constructing":[71],"fusion":[74],"bottleneck":[75],"(SFB),":[76],"CDSiT":[77,104],"can":[78],"implicitly":[79],"fuse":[80],"classify":[82,117],"with":[85],"complementary":[86],"structures":[87],"domains.":[90],"Extensive":[91],"experiments":[92],"are":[93,114],"performed":[94],"on":[95],"RadioML2016.10A":[96],"RadioML2018.01A,":[98],"results":[101],"show":[102],"that":[103,113],"outperforms":[105],"its":[106],"counterparts,":[107],"particularly":[108],"some":[110],"modes":[112],"difficult":[115],"before.":[118],"Through":[119],"ablation":[120],"experiences,":[121],"we":[122],"also":[123],"verify":[124],"effectiveness":[126],"each":[128],"module":[129],"CDSiT.":[131]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
