About the journal

Cobiss

Facta universitatis - series: Electronics and Energetics 2016 Volume 29, Issue 2, Pages: 177-191
https://doi.org/10.2298/FUEE1602177M
Full text ( 523 KB)
Cited by


Artifical neural networks in RF MEMS switch modelling

Marinković Zlatica ORCID iD icon (Faculty of Electronic Engineering, Niš)
Marković Vera (Faculty of Electronic Engineering, Niš)
Ćirić Tomislav (Faculty of Electronic Engineering, Niš)
Vietzorreck Larissa (TU München, - Lehrstuhl für Hochfrequenztechnik, München, Germany)
Pronić-Rančić Olivera ORCID iD icon (Faculty of Electronic Engineering, Niš)

The increased growth of the applications of RF MEMS switches in modern communication systems has created an increased need for their accurate and efficient models. Artificial neural networks have appeared as a fast and efficient modelling tool providing similar accuracy as standard commercial simulation packages. This paper gives an overview of the applications of artificial neural networks in modelling of RF MEMS switches, in particular of the capacitive shunt switches, proposed by the authors of the paper. Models for the most important switch characteristics in electrical and mechanical domains are considered, as well as the inverse models aimed to determine the switch bridge dimensions for specified requirements for the switch characteristics.

Keywords: actuation voltage, artificial neural networks, resonant frequency, RF MEMS, switch

Projekat Ministarstva nauke Republike Srbije, br. TR32052 i br. III-43012