{"title":"基于人工神经网络的模拟研究中子辐射对MOS器件的影响","authors":"F. Meddour, A. Meddour, M. Abdi, M. Amir","doi":"10.1109/CCEE.2018.8634508","DOIUrl":null,"url":null,"abstract":"In this work, a MOS devices model based on the artificial neural network (ANN) is proposed. This model is designed in order to use it in the neutron radiation effects. It allows us to infer several information about neutrons such as angle $\\theta$, fluence, drain source voltage (Vds), voltage between the drain and source, (Vgs) voltage between the gate and source, (Ids) current between the drain and source and the temperature. the results achieved are similar with the experimental results of the literature.","PeriodicalId":200936,"journal":{"name":"2018 International Conference on Communications and Electrical Engineering (ICCEE)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"ANN-based-modling to study the Neutron radiation effects on MOS devices\",\"authors\":\"F. Meddour, A. Meddour, M. Abdi, M. Amir\",\"doi\":\"10.1109/CCEE.2018.8634508\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this work, a MOS devices model based on the artificial neural network (ANN) is proposed. This model is designed in order to use it in the neutron radiation effects. It allows us to infer several information about neutrons such as angle $\\\\theta$, fluence, drain source voltage (Vds), voltage between the drain and source, (Vgs) voltage between the gate and source, (Ids) current between the drain and source and the temperature. the results achieved are similar with the experimental results of the literature.\",\"PeriodicalId\":200936,\"journal\":{\"name\":\"2018 International Conference on Communications and Electrical Engineering (ICCEE)\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 International Conference on Communications and Electrical Engineering (ICCEE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CCEE.2018.8634508\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 International Conference on Communications and Electrical Engineering (ICCEE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCEE.2018.8634508","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
ANN-based-modling to study the Neutron radiation effects on MOS devices
In this work, a MOS devices model based on the artificial neural network (ANN) is proposed. This model is designed in order to use it in the neutron radiation effects. It allows us to infer several information about neutrons such as angle $\theta$, fluence, drain source voltage (Vds), voltage between the drain and source, (Vgs) voltage between the gate and source, (Ids) current between the drain and source and the temperature. the results achieved are similar with the experimental results of the literature.