Vladica Đorđević, E. Cardillo, Z. Marinković, O. Pronić-Rančić, A. Caddemi, V. Markovic
{"title":"Wave approach to noise modeling of scaled on-wafer GaAs HEMTs","authors":"Vladica Đorđević, E. Cardillo, Z. Marinković, O. Pronić-Rančić, A. Caddemi, V. Markovic","doi":"10.1109/TELSKS.2017.8246296","DOIUrl":null,"url":null,"abstract":"Since the wave approach has proved to be a very efficient tool for the microwave transistor noise modeling, this paper presents its application to the noise modeling of the microwave scaled on-wafer GaAs HEMTs. For the purpose of the noise wave parameter determination, the analytical approach is used. In order to achieve the continuous extraction of the noise wave parameters over the whole frequency range, the determined values of these parameters are fitted by exploiting the artificial neural networks. The validation of the presented noise modeling approach is done by comparing the simulated and measured noise parameters.","PeriodicalId":206778,"journal":{"name":"2017 13th International Conference on Advanced Technologies, Systems and Services in Telecommunications (TELSIKS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 13th International Conference on Advanced Technologies, Systems and Services in Telecommunications (TELSIKS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TELSKS.2017.8246296","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Since the wave approach has proved to be a very efficient tool for the microwave transistor noise modeling, this paper presents its application to the noise modeling of the microwave scaled on-wafer GaAs HEMTs. For the purpose of the noise wave parameter determination, the analytical approach is used. In order to achieve the continuous extraction of the noise wave parameters over the whole frequency range, the determined values of these parameters are fitted by exploiting the artificial neural networks. The validation of the presented noise modeling approach is done by comparing the simulated and measured noise parameters.