Work

ANN Model For SiGe HBTs Constructed From Time-Domain Large-Signal Measurements

Year: 2002

Type: conference-paper

Abstract: We construct a large-signal artificial neural network (ANN) model for SiGe HBTs, directly from time-domain large-signal measurements. It is known that HBTs are very sensitive to self-heating and therefore we explicitly study the effect on the model accuracy of the incorporation of the self-heating effect in the behavioural model description. Finally, we show that this type of models can be accurate at extreme operating conditions, where classical compact models start to fail.

Source: AMS Acta (University of Bologna)

DOI: 10.6092/unibo/amsacta/139

Authors: Schreurs, D., Vandenberghe, S., Taher, H., Nauwelaers, B.

Institution: KU Leuven

Language: English

Topic: Advanced Power Amplifier Design

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: green

Funders: Vlaamse regering, National Institute of Standards and Technology

OpenAlex ID: W6568009