Scaling supply voltage of FinFET circuits is an efficient method to achieve low power dissipation. Superthreshold FinFET logic circuits can attain low power consumption with favorable performance, because FinFET devices operating on medium strong inversion regions can provide better drive strength than conventional CMOS transistors. The supply voltage of the super-threshold circuit is much larger than threshold voltage of the transistors, but it is lower than normal standard supply voltage. In this paper, basic FinFET logic gates based on static logic, DCVSL (Differential Cascode Voltage Switch Logic), PTL (Pass Transistor Logic), and TG (Transmission Gate) logic styles operating on medium strong inversion regions are investigated in terms of power consumption and delay. All circuits are simulated with HSPICE at a PTM (Predictive Technology Model) 32nm FinFET technology. The simulation results show that superthreshold FinFET logic gates operating on medium strong inversion regions attain about 41% power reduction with a penalty of only about 23%.
The favorable localization features of discrete wavelet provide a new method for detecting the mutational points of electric spark signal. In this paper, by means of discrete wavelet function called db5, using the way of 6 scales wavelet, analyzing the gathered electric spark signal and by extracting the modulus maxima of the 6 layers detailed signal coefficient, the signal's mutational points were located exactly and successfully. In addition, via the modulus maxima to calculate Lipschitz index, measuring signal's singularity, the signal's mutational time was confirmed. The result of the simulation shows that this method can detect not only the time and size effectively if the ring fire happens but also the failure of the locomotive traction dc motor, timely and precisely. In this way, the operation safety of the train is ensured.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.