{"id":"https://openalex.org/W2996570101","doi":"https://doi.org/10.1109/wcsp.2019.8927876","title":"Overfitting and Underfitting Analysis for Deep Learning Based End-to-end Communication Systems","display_name":"Overfitting and Underfitting Analysis for Deep Learning Based End-to-end Communication Systems","publication_year":2019,"publication_date":"2019-10-01","ids":{"openalex":"https://openalex.org/W2996570101","doi":"https://doi.org/10.1109/wcsp.2019.8927876","mag":"2996570101"},"language":"en","primary_location":{"id":"doi:10.1109/wcsp.2019.8927876","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wcsp.2019.8927876","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 11th International Conference on Wireless Communications and Signal Processing (WCSP)","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/A5100392967","display_name":"Haotian Zhang","orcid":"https://orcid.org/0000-0003-0478-3869"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haotian Zhang","raw_affiliation_strings":["School of Electronics and Information Technology, Sun Yat-sen University, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronics and Information Technology, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100351795","display_name":"Lin Zhang","orcid":"https://orcid.org/0000-0001-7826-2850"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lin Zhang","raw_affiliation_strings":["Shandong Provincial Key Lab. of Wireless Communication Technologies, Jinan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shandong Provincial Key Lab. of Wireless Communication Technologies, Jinan, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064657549","display_name":"Yuan Jiang","orcid":"https://orcid.org/0000-0003-4307-0562"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuan Jiang","raw_affiliation_strings":["School of Electronics and Information Technology, Sun Yat-sen University, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronics and Information Technology, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.9364,"has_fulltext":false,"cited_by_count":106,"citation_normalized_percentile":{"value":0.9548296,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":null,"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":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":0.991599977016449,"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"}},{"id":"https://openalex.org/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.9879999756813049,"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/overfitting","display_name":"Overfitting","score":0.9833052754402161},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6126071214675903},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5824154019355774},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.5676087141036987},{"id":"https://openalex.org/keywords/additive-white-gaussian-noise","display_name":"Additive white Gaussian noise","score":0.5212174654006958},{"id":"https://openalex.org/keywords/transmission","display_name":"Transmission (telecommunications)","score":0.4605070948600769},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3760796785354614},{"id":"https://openalex.org/keywords/white-noise","display_name":"White noise","score":0.27461081743240356},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.2610623836517334},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.13178521394729614}],"concepts":[{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.9833052754402161},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6126071214675903},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5824154019355774},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.5676087141036987},{"id":"https://openalex.org/C169334058","wikidata":"https://www.wikidata.org/wiki/Q353292","display_name":"Additive white Gaussian noise","level":3,"score":0.5212174654006958},{"id":"https://openalex.org/C761482","wikidata":"https://www.wikidata.org/wiki/Q118093","display_name":"Transmission (telecommunications)","level":2,"score":0.4605070948600769},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3760796785354614},{"id":"https://openalex.org/C112633086","wikidata":"https://www.wikidata.org/wiki/Q381287","display_name":"White noise","level":2,"score":0.27461081743240356},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2610623836517334},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.13178521394729614}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/wcsp.2019.8927876","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wcsp.2019.8927876","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 11th International Conference on Wireless Communications and Signal Processing (WCSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.800000011920929,"id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1559601530","https://openalex.org/W1904365287","https://openalex.org/W2272847350","https://openalex.org/W2398827528","https://openalex.org/W2557283755","https://openalex.org/W2734408173","https://openalex.org/W2775795276","https://openalex.org/W2794455536","https://openalex.org/W2795247881","https://openalex.org/W2907127169","https://openalex.org/W2963290405","https://openalex.org/W2963408536","https://openalex.org/W2964121744","https://openalex.org/W2991019415"],"related_works":["https://openalex.org/W1574414179","https://openalex.org/W4362597605","https://openalex.org/W4297676672","https://openalex.org/W4281702477","https://openalex.org/W2922073769","https://openalex.org/W4378510483","https://openalex.org/W2490526372","https://openalex.org/W2989932438","https://openalex.org/W4387297750","https://openalex.org/W2186333919"],"abstract_inverted_index":{"In":[0,79],"this":[1],"paper,":[2],"we":[3,15,84,128],"study":[4],"the":[5,17,20,28,31,37,42,46,60,65,72,88,101,108,115,132,137,145,154,163,168],"deep":[6],"learning":[7],"(DL)":[8],"based":[9,39],"end-":[10],"to-end":[11],"transmission":[12,43,73,151],"systems,":[13,83],"then":[14],"present":[16],"analysis":[18,149],"for":[19,150],"underfitting":[21,66,104,146],"and":[22,67,91,105,147,161],"overfitting":[23,68,106,138,148],"phenomena":[24],"which":[25],"happen":[26],"during":[27],"training":[29,61],"of":[30,76,93,103,114],"neural":[32],"networks":[33],"(NNs).":[34],"Different":[35],"from":[36],"DL":[38],"image":[40],"processing,":[41],"systems":[44,152],"require":[45],"bit":[47,118],"error":[48,109],"rate":[49,110],"to":[50,86,99,119,130,135,143],"be":[51],"as":[52,54],"low":[53],"10\u20134to":[55],"achieve":[56],"high":[57],"reliability,":[58],"thus":[59],"errors":[62],"induced":[63],"by":[64,166],"may":[69],"greatly":[70],"degrade":[71],"reliability":[74],"performances":[75,111,165],"DL-based":[77,81],"communications.":[78],"considered":[80],"communication":[82],"propose":[85,129],"use":[87],"average,":[89],"variance":[90],"minimum":[92,96],"transmitted":[94],"signals'":[95],"Euclidean":[97],"distance":[98],"estimate":[100],"effects":[102],"on":[107],"in":[112],"terms":[113],"energy":[116],"per":[117],"noise":[120,158],"power":[121],"spectral":[122],"ratio":[123],"Eb/":[124],"Noof":[125],"signals.":[126],"Furthermore,":[127],"apply":[131],"regularization":[133],"scheme":[134],"alleviate":[136],"issue.":[139],"Simulations":[140],"are":[141],"performed":[142],"demonstrate":[144],"over":[153],"additive":[155],"white":[156],"Gaussian":[157],"(AWGN)":[159],"channel,":[160],"validate":[162],"improved":[164],"applying":[167],"regularization.":[169]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":15},{"year":2024,"cited_by_count":22},{"year":2023,"cited_by_count":31},{"year":2022,"cited_by_count":18},{"year":2021,"cited_by_count":13},{"year":2020,"cited_by_count":5}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
