{"title":"基于神经网络的RF-DC转换电路在线加速自动设计研究","authors":"Takuma Akada, K. Fujimori","doi":"10.23919/ISAP47053.2021.9391324","DOIUrl":null,"url":null,"abstract":"The design method of RF-DC conversion circuits for wireless power transmission is discussed. The extent to which circuit properties can be estimated using convolutional neural networks is discussed in this study. In order to use an automatic design method for circuit design, it is a problem that it takes time for electromagnetic field analysis. It is shown that the proposed method may make it possible to design circuits in a realistic time.","PeriodicalId":165901,"journal":{"name":"2020 International Symposium on Antennas and Propagation (ISAP)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A study on an online acceleration of automatic design of RF-DC conversion circuit using neural networks\",\"authors\":\"Takuma Akada, K. Fujimori\",\"doi\":\"10.23919/ISAP47053.2021.9391324\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The design method of RF-DC conversion circuits for wireless power transmission is discussed. The extent to which circuit properties can be estimated using convolutional neural networks is discussed in this study. In order to use an automatic design method for circuit design, it is a problem that it takes time for electromagnetic field analysis. It is shown that the proposed method may make it possible to design circuits in a realistic time.\",\"PeriodicalId\":165901,\"journal\":{\"name\":\"2020 International Symposium on Antennas and Propagation (ISAP)\",\"volume\":\"17 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-01-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 International Symposium on Antennas and Propagation (ISAP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23919/ISAP47053.2021.9391324\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 International Symposium on Antennas and Propagation (ISAP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/ISAP47053.2021.9391324","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A study on an online acceleration of automatic design of RF-DC conversion circuit using neural networks
The design method of RF-DC conversion circuits for wireless power transmission is discussed. The extent to which circuit properties can be estimated using convolutional neural networks is discussed in this study. In order to use an automatic design method for circuit design, it is a problem that it takes time for electromagnetic field analysis. It is shown that the proposed method may make it possible to design circuits in a realistic time.
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