{"title":"phemt的信号和噪声神经模型","authors":"V. Markovic, Z. Marinković","doi":"10.1109/NEUREL.2002.1057995","DOIUrl":null,"url":null,"abstract":"Low-noise pHEMT transistors, that have excellent performances at microwave frequencies, can be described by their scattering and noise parameters. In this paper, a pHEMT neural model, based on multilayer perceptron neural networks is proposed. The obtained neural models can predict transistor's signal and noise performances very efficiently and accurately for a broad range of bias conditions in the operating frequency range.","PeriodicalId":347066,"journal":{"name":"6th Seminar on Neural Network Applications in Electrical Engineering","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2002-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Signal and noise neural models of pHEMTs\",\"authors\":\"V. Markovic, Z. Marinković\",\"doi\":\"10.1109/NEUREL.2002.1057995\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Low-noise pHEMT transistors, that have excellent performances at microwave frequencies, can be described by their scattering and noise parameters. In this paper, a pHEMT neural model, based on multilayer perceptron neural networks is proposed. The obtained neural models can predict transistor's signal and noise performances very efficiently and accurately for a broad range of bias conditions in the operating frequency range.\",\"PeriodicalId\":347066,\"journal\":{\"name\":\"6th Seminar on Neural Network Applications in Electrical Engineering\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2002-12-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"6th Seminar on Neural Network Applications in Electrical Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NEUREL.2002.1057995\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"6th Seminar on Neural Network Applications in Electrical Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NEUREL.2002.1057995","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Low-noise pHEMT transistors, that have excellent performances at microwave frequencies, can be described by their scattering and noise parameters. In this paper, a pHEMT neural model, based on multilayer perceptron neural networks is proposed. The obtained neural models can predict transistor's signal and noise performances very efficiently and accurately for a broad range of bias conditions in the operating frequency range.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
