RF MEMS Double Beam Lateral Switch Characteristics Analysis Using Neural Network

This paper presents Artificial Neural Network (ANN) implementation for Mechanical modeling of Radio Frequency Micro Electro Mechanical System (RF MEMS) lateral double beam switch. We propose an efficient approach based on ANN for analyzing the static and dynamic characteristics of RF MEMS lateral switch by calculating its characteristics parameters. ANN model were trained with five learning algorithms and the results from the neural model trained by Levenberg-Marquardt back propagation algorithm are highly agreed with theoretical results. The neural network shows better results with highest correlation coefficient (0.5844) along with lowest root mean square error (0.0539).