首页|New Findings from National Center for Scientific Research (CNRS) in the Area of Machine Learning Described (Machine Learning- Based Modeling of Hot Carrier Injec tion in 40 nm CMOS Transistors)
New Findings from National Center for Scientific Research (CNRS) in the Area of Machine Learning Described (Machine Learning- Based Modeling of Hot Carrier Injec tion in 40 nm CMOS Transistors)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New study results on artificial intell igence have been published. According to news reporting originating from Montpel lier, France, by NewsRx correspondents, research stated, “This paper presents a machine-learning-based approach for the degradation modeling of hot carrier inje ction in metaloxide- semiconductor field-effect transistors (MOSFETs).” Financial supporters for this research include Technological Research Council of Turkey Through Project Tub itak 1001. The news reporters obtained a quote from the research from National Center for S cientific Research (CNRS): “Stress measurement data have been employed at variou s stress conditions of both n- and p- MOSFETs with different channel geometries. Gaussian process regression algorithm is preferred to model the post-stress char acteristics of the drain-source current, the threshold voltage, and the drain-so urce conductance. The model outcomes have been compared with the actual measurem ents, and the accuracy of the generated models has been demonstrated across the test data by providing the appropriate statistics metrics. Finally, case studies of degradation estimation have been considered involving the usage of machine-l earning-based models on transistors with different channel geometries or subject ed to distinct stress conditions.”
National Center for Scientific Research (CNRS)MontpellierFranceEuropeCyborgsEmerging TechnologiesMachine Lea rning
NETL
NSTL
