{"id":"https://openalex.org/W2892721256","doi":"https://doi.org/10.1109/icton.2018.8473703","title":"Simultaneous Monitoring of Chromatic Dispersion and Optical Signal to Noise Ratio in Optical Network Using Asynchronous Delay Tap Sampling and Convolutional Neural Network (Deep Learning)","display_name":"Simultaneous Monitoring of Chromatic Dispersion and Optical Signal to Noise Ratio in Optical Network Using Asynchronous Delay Tap Sampling and Convolutional Neural Network (Deep Learning)","publication_year":2018,"publication_date":"2018-07-01","ids":{"openalex":"https://openalex.org/W2892721256","doi":"https://doi.org/10.1109/icton.2018.8473703","mag":"2892721256"},"language":"en","primary_location":{"id":"doi:10.1109/icton.2018.8473703","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icton.2018.8473703","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 20th International Conference on Transparent Optical Networks (ICTON)","raw_type":"proceedings-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/A5031928069","display_name":"Tomasz Mrozek","orcid":"https://orcid.org/0000-0002-2821-2908"},"institutions":[{"id":"https://openalex.org/I4210125529","display_name":"National Institute of Telecommunications","ror":"https://ror.org/03053v606","country_code":"PL","type":"facility","lineage":["https://openalex.org/I4210125529"]}],"countries":["PL"],"is_corresponding":true,"raw_author_name":"Tomasz Mrozek","raw_affiliation_strings":["Institute of Telecommunications, Warsaw, Poland"],"affiliations":[{"raw_affiliation_string":"Institute of Telecommunications, Warsaw, Poland","institution_ids":["https://openalex.org/I4210125529"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5031928069"],"corresponding_institution_ids":["https://openalex.org/I4210125529"],"apc_list":null,"apc_paid":null,"fwci":0.6438,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.71258327,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10232","display_name":"Optical Network Technologies","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10232","display_name":"Optical Network Technologies","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9975000023841858,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10767","display_name":"Advanced Photonic Communication Systems","score":0.9944000244140625,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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":0.6644839644432068},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5894179940223694},{"id":"https://openalex.org/keywords/asynchronous-communication","display_name":"Asynchronous communication","score":0.5674890875816345},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.49304959177970886},{"id":"https://openalex.org/keywords/optical-performance-monitoring","display_name":"Optical performance monitoring","score":0.47214818000793457},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.4717721939086914},{"id":"https://openalex.org/keywords/dispersion","display_name":"Dispersion (optics)","score":0.47010037302970886},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4494037330150604},{"id":"https://openalex.org/keywords/signal-to-noise-ratio","display_name":"Signal-to-noise ratio (imaging)","score":0.4365251660346985},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4214385747909546},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.41952255368232727},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.36306560039520264},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.2661782503128052},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.20914927124977112},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.1895613670349121},{"id":"https://openalex.org/keywords/wavelength-division-multiplexing","display_name":"Wavelength-division multiplexing","score":0.08993586897850037},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.07271042466163635}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6644839644432068},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5894179940223694},{"id":"https://openalex.org/C151319957","wikidata":"https://www.wikidata.org/wiki/Q752739","display_name":"Asynchronous communication","level":2,"score":0.5674890875816345},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.49304959177970886},{"id":"https://openalex.org/C26840048","wikidata":"https://www.wikidata.org/wiki/Q7098880","display_name":"Optical performance monitoring","level":4,"score":0.47214818000793457},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.4717721939086914},{"id":"https://openalex.org/C177562468","wikidata":"https://www.wikidata.org/wiki/Q182893","display_name":"Dispersion (optics)","level":2,"score":0.47010037302970886},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4494037330150604},{"id":"https://openalex.org/C13944312","wikidata":"https://www.wikidata.org/wiki/Q7512748","display_name":"Signal-to-noise ratio (imaging)","level":2,"score":0.4365251660346985},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4214385747909546},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.41952255368232727},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36306560039520264},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.2661782503128052},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.20914927124977112},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.1895613670349121},{"id":"https://openalex.org/C160724564","wikidata":"https://www.wikidata.org/wiki/Q1620670","display_name":"Wavelength-division multiplexing","level":3,"score":0.08993586897850037},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.07271042466163635},{"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/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C6260449","wikidata":"https://www.wikidata.org/wiki/Q41364","display_name":"Wavelength","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icton.2018.8473703","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icton.2018.8473703","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 20th International Conference on Transparent Optical Networks (ICTON)","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":7,"referenced_works":["https://openalex.org/W2046997552","https://openalex.org/W2052534188","https://openalex.org/W2083910333","https://openalex.org/W2103627610","https://openalex.org/W2112796928","https://openalex.org/W2146225156","https://openalex.org/W6675627721"],"related_works":["https://openalex.org/W2116677773","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3167935049","https://openalex.org/W3103566983","https://openalex.org/W3029198973","https://openalex.org/W2099708942"],"abstract_inverted_index":{"The":[0],"article":[1],"presents":[2],"the":[3,21,40,45,49,54,59,73,82,85,96,108,123,126,129,147,155],"possibilities":[4],"of":[5,23,42,56,61,65,75,111,122,128,137,157],"using":[6,81],"Asynchronous":[7],"Delay":[8],"Tap":[9],"Sampling":[10],"(ADTS)":[11],"and":[12,27,77,103],"Convolutional":[13],"Neural":[14],"Network":[15],"(CNN)":[16],"methods":[17],"to":[18,30,94,153],"simultaneously":[19,70],"monitor":[20],"parameters":[22],"Chromatic":[24],"Dispersion":[25],"(CD)":[26],"Optical":[28],"Signal":[29],"Noise":[31],"Ratio":[32],"(OSNR),":[33],"which":[34,52],"have":[35],"a":[36,63,119,144],"significant":[37],"impact":[38],"on":[39],"quality":[41],"transmission":[43],"in":[44,58,92],"optical":[46],"network.":[47],"Using":[48],"ADTS":[50],"method,":[51],"allows":[53],"presentation":[55],"impairments":[57,102,159],"form":[60],"characteristics,":[62],"set":[64,149],"10000":[66],"images":[67],"was":[68,89],"generated":[69],"disturbed":[71],"by":[72],"combination":[74],"CD":[76],"OSNR":[78],"phenomena.":[79],"Next,":[80],"CNN":[83],"algorithms,":[84],"network":[86],"learning":[87],"process":[88],"carried":[90],"out":[91],"order":[93],"obtain":[95],"best":[97],"possible":[98],"model":[99],"for":[100,150],"recognizing":[101],"predicting":[104],"their":[105],"values.":[106],"After":[107],"appropriate":[109,161],"number":[110],"tests,":[112],"very":[113],"good":[114],"results":[115],"were":[116],"obtained":[117],"ensuring":[118],"high":[120],"adjustment":[121],"models":[124],"at":[125],"level":[127],"matching":[130],"factor":[131],"R":[132],"<sup":[133],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[134],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">2</sup>":[135],"(Coefficient":[136],"determination)":[138],"above":[139],"0.995.":[140],"Models":[141],"with":[142],"such":[143],"fit":[145],"fulfil":[146],"requirements":[148],"monitoring":[151],"systems":[152],"recognize":[154],"value":[156],"occurring":[158],"within":[160],"accuracy":[162],"limits.":[163]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
