Neuro-fuzzy network approach for modeling submicron MOSFETs: application to MOSFET subcircuit simulation
نویسندگان
چکیده
A neuro-fuzzy network approach is developed to model the nonlinear behavior of submicron metal-oxide semiconductor field-effect transistors (MOSFETs). The proposed model is trained and implemented as a MOSFET in a software environment. The training data are obtained through various simulations of a MOSFET Berkeley short channel insulated-gate field-effect transistor model 3 (BSIM3) in HSPICE, and the trained model is utilized to simulate the MOSFET device. The obtained result shows good and noticeable agreement between the numerical result of the original model in HSPICE and the neuro-fuzzy approach in the device and subcircuit modeling.
منابع مشابه
A Simple General-purpose I-V Model for All Operating Modes of Deep Submicron MOSFETs
A simple general-purpose I-V model for all operating modes of deep-submicron MOSFETs is presented. Considering the most dominant short channel effects with simple equations including few extra parameters, a reasonable trade-off between simplicity and accuracy is established. To further improve the accuracy, model parameters are optimized over various channel widths and full range of operating v...
متن کاملMosfet Modeling
A n improved SPICE model has been developed by Fairchild engineers for the simulation of trench power devices using the BSIM3 MOSFET model. The new model architecture seeks to eliminate shortcomings in the level 1 and level 3 subcircuit methods used extensively for modeling MOSFETs in power circuits. The new model offers excellent correlation to product data, transistor scaling not possible wit...
متن کاملA New Physical Modeling of Parasitic Capacitances of Deep-Submicron LDD MOSFETs
In mixed circuit simulation, the estimation of parasitic capacitances of deep-submicron MOSFETs is very important. With the continuous scaling of the devices, the extrinsic capacitance, i.e. the overlap and fringing capacitances become a growing fraction of the total gate capacitance. We found the major existing models do not predict correctly the overlap capacitance and the inner fringing capa...
متن کاملThe efficiency of Artificial Neural Network, Neuro-Fuzzy and Multivariate Regression models for runoff and erosion simulation using rainfall simulator
1- INTRODUCTION According to the complexity of environmental factors related to erosion and runoff, correct simulation of these variables find importance under rain intensity domain of watershed areas. Although modeling of erosion and runoff by Artificial Neural Network and Neuro-Fuzzy based on rainfall-runoff and discharge-sediment models were widely applied by researchers, scrutinizing Arti...
متن کاملQuantum Corrections in 3-D Drift Diffusion Simulations of Decanano MOSFETs Using an Effective Potential
As MOSFET devices are aggressively scaled into the deep submicron regime quantum mechanical effects become increasingly important. We compare the recently proposed effective potential formalism with the density gradient approach for first order quantum simulations of sub 0.1μm MOSFETs within a modified drift diffusion framework.
متن کامل