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Artificial neural networks for efficient RF MEMS modeling

In this contribution we will show how artificial neural networks can be efficiently used to build models of RF MEMS components or to optimize them without enhanced numerical efforts. The method is especially interesting for designers and technologists, who want to modify or optimize switch parameters for a fixed technology without using heavy simulation tools. As examples the fast and accurate calculation of scattering parameters for an ohmic switch dependent on 4 different geometrical dimensions over frequency is shown. The second example is the derivation of some lateral dimensions for the resonant frequency of a capacitive switch without using optimization routines.