基于级联人工神经网络的轻型光学星座建模

D. Sequeira, M. Ruiz, N. Costa, A. Napoli, J. Pedro, Luis Velasco
{"title":"基于级联人工神经网络的轻型光学星座建模","authors":"D. Sequeira, M. Ruiz, N. Costa, A. Napoli, J. Pedro, Luis Velasco","doi":"10.1109/ecoc52684.2021.9606054","DOIUrl":null,"url":null,"abstract":"A lightweight optical constellations modeling method based on concatenating ANNs is proposed. Statistical validation of the reproduced constellations is shown. The method accelerates data generation and facilitates detecting (un)intentioned misconfigurations, among others.","PeriodicalId":117375,"journal":{"name":"2021 European Conference on Optical Communication (ECOC)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Lightweight Optical Constellation Modeling by Concatenating Artificial Neural Networks\",\"authors\":\"D. Sequeira, M. Ruiz, N. Costa, A. Napoli, J. Pedro, Luis Velasco\",\"doi\":\"10.1109/ecoc52684.2021.9606054\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A lightweight optical constellations modeling method based on concatenating ANNs is proposed. Statistical validation of the reproduced constellations is shown. The method accelerates data generation and facilitates detecting (un)intentioned misconfigurations, among others.\",\"PeriodicalId\":117375,\"journal\":{\"name\":\"2021 European Conference on Optical Communication (ECOC)\",\"volume\":\"49 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-09-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 European Conference on Optical Communication (ECOC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ecoc52684.2021.9606054\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 European Conference on Optical Communication (ECOC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ecoc52684.2021.9606054","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

提出了一种基于串联人工神经网络的轻型光学星座建模方法。给出了再现星座的统计验证。该方法加速了数据生成,便于检测(非)有意的错误配置等。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Lightweight Optical Constellation Modeling by Concatenating Artificial Neural Networks
A lightweight optical constellations modeling method based on concatenating ANNs is proposed. Statistical validation of the reproduced constellations is shown. The method accelerates data generation and facilitates detecting (un)intentioned misconfigurations, among others.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信