In this paper an artificial neural network approach for nonlinear modelling of a 10-W LDMOSFET is presented. The model extraction is based on DC and scattering parameter measurements. In particular, artificial neural networks are used to model the dependence of both DC drain current and intrinsic capacitances with respect to the intrinsic gate and drain voltages. The model validation is successfully achieved by comparing the simulation results with time-domain nonlinear measurements.

A neural network approach for nonlinear modelling of LDMOSFETs

RAFFO, Antonio;BOSI, Gianni;VANNINI, Giorgio;
2014

Abstract

In this paper an artificial neural network approach for nonlinear modelling of a 10-W LDMOSFET is presented. The model extraction is based on DC and scattering parameter measurements. In particular, artificial neural networks are used to model the dependence of both DC drain current and intrinsic capacitances with respect to the intrinsic gate and drain voltages. The model validation is successfully achieved by comparing the simulation results with time-domain nonlinear measurements.
2014
978-1-4799-3454-6
artificial neural network (ANN); high-power transistor; laterally diffused MOS (LDMOS); nonlinear measurements; nonlinear modelling; Hardware and Architecture; Electrical and Electronic Engineering
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11392/2336364
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