{"title":"Deep learning as a highly efficient tool for digital signal processing design","authors":"Andrey Pryamikov","doi":"10.1038/s41377-024-01599-8","DOIUrl":null,"url":null,"abstract":"<p>The backpropagation algorithm, the most widely used algorithm for training artificial neural networks, can be effectively applied to the development of digital signal processing schemes in the optical fiber transmission systems. Digital signal processing as a deep learning framework can lead to a new highly efficient paradigm for cost-effective digital signal processing designes with low complexity.</p>","PeriodicalId":18069,"journal":{"name":"Light-Science & Applications","volume":null,"pages":null},"PeriodicalIF":20.6000,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Light-Science & Applications","FirstCategoryId":"1089","ListUrlMain":"https://doi.org/10.1038/s41377-024-01599-8","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"OPTICS","Score":null,"Total":0}
引用次数: 0
Abstract
The backpropagation algorithm, the most widely used algorithm for training artificial neural networks, can be effectively applied to the development of digital signal processing schemes in the optical fiber transmission systems. Digital signal processing as a deep learning framework can lead to a new highly efficient paradigm for cost-effective digital signal processing designes with low complexity.
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