A neural network approach for nonlinear modelling of LDMOSFETs

Author

Marinkovic, Zlatica ; Crupi, Giovanni ; Raffo, Antonio ; Bosi, Gianni ; Avolio, Gustavo ; Markovic, Vera ; Caddemi, Alina ; Vannini, Giorgio ; Schreurs, Dominique M. M.-P

Author_Institution

Fac. of Electron. Eng., Univ. of Nis, Niš, Serbia

fYear

2014

fDate

2-4 April 2014

Firstpage

1

Lastpage

3

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.

Keywords

MOSFET; S-parameters; electronic engineering computing; neural nets; semiconductor device models; DC drain current; LDMOSFET; artificial neural network; model extraction; model validation; nonlinear modelling; power 10 W; scattering parameter measurements; time-domain nonlinear measurements; Artificial neural networks; Computational modeling; Integrated circuit modeling; Microwave transistors; Transistors; Voltage measurement; artificial neural network (ANN); high-power transistor; laterally diffused MOS (LDMOS); nonlinear measurements; nonlinear modelling;

fLanguage

English

Publisher

ieee

Conference_Titel

Integrated Nonlinear Microwave and Millimetre-wave Circuits (INMMiC), 2014 International Workshop on

Conference_Location

Leuven

Type

conf

DOI

10.1109/INMMIC.2014.6815074

Filename

6815074