{"title":"非线性吸收优化光学卷积","authors":"J. George, Maria Gorgone-Solyanik, V. Sorger","doi":"10.23919/MOC52031.2021.9598149","DOIUrl":null,"url":null,"abstract":"Convolution is an essential operation in signal processing and has found applications in convolutional neural networks. All-optical convolution is challenged by small nonlinear coefficients. Two configurations for all-optical convolution with nonlinear absorption are analysed and simulated to identify parameters for optimizing signal-to-noise.","PeriodicalId":355935,"journal":{"name":"2021 26th Microoptics Conference (MOC)","volume":"87 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Optimizing Optical Convolution with Nonlinear Absorption\",\"authors\":\"J. George, Maria Gorgone-Solyanik, V. Sorger\",\"doi\":\"10.23919/MOC52031.2021.9598149\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Convolution is an essential operation in signal processing and has found applications in convolutional neural networks. All-optical convolution is challenged by small nonlinear coefficients. Two configurations for all-optical convolution with nonlinear absorption are analysed and simulated to identify parameters for optimizing signal-to-noise.\",\"PeriodicalId\":355935,\"journal\":{\"name\":\"2021 26th Microoptics Conference (MOC)\",\"volume\":\"87 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-09-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 26th Microoptics Conference (MOC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23919/MOC52031.2021.9598149\",\"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 26th Microoptics Conference (MOC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/MOC52031.2021.9598149","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimizing Optical Convolution with Nonlinear Absorption
Convolution is an essential operation in signal processing and has found applications in convolutional neural networks. All-optical convolution is challenged by small nonlinear coefficients. Two configurations for all-optical convolution with nonlinear absorption are analysed and simulated to identify parameters for optimizing signal-to-noise.