{"title":"一种射频电路中变压器参数自动提取及可扩展建模方法","authors":"Jian Yao, Zuochang Ye, Yan Wang","doi":"10.1109/RFIC.2013.6569521","DOIUrl":null,"url":null,"abstract":"Summary form only given. In this paper, an automatic parameter extraction and scalable modeling method for transformer with 2π-based equivalent circuit-topology is established for the first time. In contrast to traditional optimization extraction, the adaptive boundary compression technique, combining a new correlated parameter extraction method with the neighboring geometry parameters, is introduced. The method is validated by 42 industry transformers and both accuracy and scalability have been achieved.","PeriodicalId":203521,"journal":{"name":"2013 IEEE Radio Frequency Integrated Circuits Symposium (RFIC)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"An automatic parameter extraction and scalable modeling method for transformers in RF circuit\",\"authors\":\"Jian Yao, Zuochang Ye, Yan Wang\",\"doi\":\"10.1109/RFIC.2013.6569521\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Summary form only given. In this paper, an automatic parameter extraction and scalable modeling method for transformer with 2π-based equivalent circuit-topology is established for the first time. In contrast to traditional optimization extraction, the adaptive boundary compression technique, combining a new correlated parameter extraction method with the neighboring geometry parameters, is introduced. The method is validated by 42 industry transformers and both accuracy and scalability have been achieved.\",\"PeriodicalId\":203521,\"journal\":{\"name\":\"2013 IEEE Radio Frequency Integrated Circuits Symposium (RFIC)\",\"volume\":\"9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-06-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 IEEE Radio Frequency Integrated Circuits Symposium (RFIC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/RFIC.2013.6569521\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE Radio Frequency Integrated Circuits Symposium (RFIC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RFIC.2013.6569521","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An automatic parameter extraction and scalable modeling method for transformers in RF circuit
Summary form only given. In this paper, an automatic parameter extraction and scalable modeling method for transformer with 2π-based equivalent circuit-topology is established for the first time. In contrast to traditional optimization extraction, the adaptive boundary compression technique, combining a new correlated parameter extraction method with the neighboring geometry parameters, is introduced. The method is validated by 42 industry transformers and both accuracy and scalability have been achieved.