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.File in questo prodotto:
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