Coupling-of-Modes Parameters Extraction by Using an Inverse Artificial Neural Network Design

The coupling-of-modes (COM) theory has been widely used in design and analysis of surface acoustic waves (SAW) devices since 1980's, especially for developing radio frequency (RF) passband filters. The characterization of COM model or the extraction of COM parameters is a crucial step for the design of SAW devices, which is normally supported by perturbation, variational or empirical methods. In this paper, we would like to present a novel solution of COM parameters extraction by using artificial intelligence (AI) technology with an inverse artificial neural network design. This method shows the possibility of using AI technology in SAW devices design and analysis, with high efficiency and accuracy.