HYBRID NEURAL LUMPED ELEMENT APPROACH IN INVERSE MODELING OF RF MEMS SWITCHES

Tomislav Ciric, Zlatica Marinković, Rohan Dhuri, Olivera Pronić-Rančić, Vera Marković

DOI Number
10.2298/FUEE2001027C
First page
027
Last page
036

Abstract


RF MEMS switches have been efficiently exploited in various applications in communication systems. As the dimensions of the switch bridge influence the switch behaviour, during the design of a switch it is necessary to perform inverse modeling, i.e. to determine the bridge dimensions to ensure the desired switch characteristics, such as the resonant frequency. In this paper a novel inverse modeling approach based on combination of artificial neural networks and a lumped element circuit model has been considered. This approach allows determination of the bridge fingered part length for the given resonant frequency and the bridge solid part length, generating at the same time values of the elements of the switch lumped element model. Validity of the model is demonstrated by appropriate numerical examples.


Keywords

Artificial neural networks, inverse modeling, lumped element model, RF MEMS switch.

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References


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