{"title":"基于TDR和CNN技术的高效夹具移除嵌入式建模方法","authors":"Si-Yao Tang;Xing-Chang Wei;Richard Xian-Ke Gao","doi":"10.1109/TSIPI.2025.3560949","DOIUrl":null,"url":null,"abstract":"<italic>S</i>-parameters are typically employed in equivalent circuit (EC) modeling of electronic devices. However, for existing modeling procedures, the impact of fixtures on <italic>S</i>-parameter measurement cannot be neglected and needs to be eliminated through de-embedding before modeling. This letter proposes a new approach that integrates fixture removal into the modeling procedure by combining time-domain reflection and convolutional neural network techniques. The proposed approach bypasses the need for separate de-embedding, allowing for direct derivation of the EC model. Different to the traditional modeling procedure, its advantages in simplifying the modeling procedure and avoiding the errors introduced by de-embedding have been validated by the physical measurement.","PeriodicalId":100646,"journal":{"name":"IEEE Transactions on Signal and Power Integrity","volume":"4 ","pages":"132-135"},"PeriodicalIF":0.0000,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An Efficient Fixture Removal Embedded Modeling Method Based on TDR and CNN Technique\",\"authors\":\"Si-Yao Tang;Xing-Chang Wei;Richard Xian-Ke Gao\",\"doi\":\"10.1109/TSIPI.2025.3560949\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<italic>S</i>-parameters are typically employed in equivalent circuit (EC) modeling of electronic devices. However, for existing modeling procedures, the impact of fixtures on <italic>S</i>-parameter measurement cannot be neglected and needs to be eliminated through de-embedding before modeling. This letter proposes a new approach that integrates fixture removal into the modeling procedure by combining time-domain reflection and convolutional neural network techniques. The proposed approach bypasses the need for separate de-embedding, allowing for direct derivation of the EC model. Different to the traditional modeling procedure, its advantages in simplifying the modeling procedure and avoiding the errors introduced by de-embedding have been validated by the physical measurement.\",\"PeriodicalId\":100646,\"journal\":{\"name\":\"IEEE Transactions on Signal and Power Integrity\",\"volume\":\"4 \",\"pages\":\"132-135\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-04-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Signal and Power Integrity\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10965361/\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Signal and Power Integrity","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/10965361/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Efficient Fixture Removal Embedded Modeling Method Based on TDR and CNN Technique
S-parameters are typically employed in equivalent circuit (EC) modeling of electronic devices. However, for existing modeling procedures, the impact of fixtures on S-parameter measurement cannot be neglected and needs to be eliminated through de-embedding before modeling. This letter proposes a new approach that integrates fixture removal into the modeling procedure by combining time-domain reflection and convolutional neural network techniques. The proposed approach bypasses the need for separate de-embedding, allowing for direct derivation of the EC model. Different to the traditional modeling procedure, its advantages in simplifying the modeling procedure and avoiding the errors introduced by de-embedding have been validated by the physical measurement.