A linear statistical FET model using principal component analysis

Author

Purviance, John E. ; Petzold, Mark C. ; Potratz, Clarence

Author_Institution

Dept. of Electr. Eng., Idaho Univ., Moscow, ID, USA

Volume

37

Issue

9

fYear

1989

fDate

9/1/1989 12:00:00 AM

Firstpage

1389

Lastpage

1394

Abstract

An important issue in statistical circuit design, other than the algorithms themselves, is the development of efficient, statistically valid element models. The authors first discuss what features are needed for a good statistical model. The standard FET model is shown to be difficult to use in a statistical simulation, due to the nonlinear relation between FET S-parameters and model parameters. A linear statistical FET model is then proposed that is based on principal component analysis. This linear model gives uncorrelated model parameters. In an example using measured S-parameter data from ninety 0.5-μm GaAs FETs, 13 uncorrelated model parameters were needed to model the data from 1 to 11 GHz and at one bias. Simulation using this linear model and issues relating to bias are discussed

Keywords

S-parameters; field effect transistors; semiconductor device models; solid-state microwave devices; statistical analysis; 0.5 micron; 1 to 11 GHz; GaAs; S-parameter data; SHF; bias; element models; linear statistical FET model; microwave devices; principal component analysis; statistical circuit design; statistical simulation; uncorrelated model parameters; Circuit simulation; Circuit synthesis; Density functional theory; Design optimization; FETs; Gallium arsenide; Principal component analysis; Scattering parameters; Statistics; Yield estimation;

fLanguage

English

Journal_Title

Microwave Theory and Techniques, IEEE Transactions on

Publisher

ieee

ISSN

0018-9480

Type

jour

DOI

10.1109/22.32222

Filename

32222