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.
Artifical neural networks in RF MEMS switch modelling