{"title":"Neural models for the active microwave devices","authors":"B. Karlik","doi":"10.1109/LFNM.2003.1246151","DOIUrl":null,"url":null,"abstract":"Artificial neural networks are emerging as a powerful technology for RF and microwave characterization, modeling, and design. Neuron modeler is the first software in the industry that embraces this technology with complete RF and microwave orientation. It helps you to immediately start developing neural models for RF/microwave components and circuits and helps to provide neural models for your simulators. The device is modeled by a black box whose small signal and noise parameters are evaluated through a neural network, based upon the fitting of both of these parameters for the multiple bias or configuration. In this study, two types of neural network were compared for the existing device modeling technique. The concurrent modeling procedure does not require solving device physics equations repeatedly during optimization.","PeriodicalId":368970,"journal":{"name":"5th International Workshop on Laser and Fiber-Optical Networks Modeling, 2003. Proceedings of LFNM 2003.","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2003-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"5th International Workshop on Laser and Fiber-Optical Networks Modeling, 2003. Proceedings of LFNM 2003.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/LFNM.2003.1246151","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
Artificial neural networks are emerging as a powerful technology for RF and microwave characterization, modeling, and design. Neuron modeler is the first software in the industry that embraces this technology with complete RF and microwave orientation. It helps you to immediately start developing neural models for RF/microwave components and circuits and helps to provide neural models for your simulators. The device is modeled by a black box whose small signal and noise parameters are evaluated through a neural network, based upon the fitting of both of these parameters for the multiple bias or configuration. In this study, two types of neural network were compared for the existing device modeling technique. The concurrent modeling procedure does not require solving device physics equations repeatedly during optimization.