Artifical neural networks in RF MEMS switch modelling | Zendy

Zlatica Marinković | Zendy; Vera Marković | Zendy; Tomislav Ćirić | Zendy; Larissa Vietzorreck | Zendy; Olivera PronićRančić | Zendy

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Artifical neural networks in RF MEMS switch modelling

Author(s) -

Zlatica Marinković,

Vera Marković,

Tomislav Ćirić,

Larissa Vietzorreck,

Olivera PronićRančić

Publication year - 2016

Publication title -

facta universitatis - series electronics and energetics

Language(s) - English

Resource type - Journals

eISSN - 2217-5997

pISSN - 0353-3670

DOI - 10.2298/fuee1602177m

Subject(s) - microelectromechanical systems , artificial neural network , computer science , electronic engineering , capacitive sensing , engineering , control engineering , electrical engineering , artificial intelligence , nanotechnology , materials science

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.

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