Neuro-fuzzy approach in microwave filter tuning

This paper describes a method of microwave filter tuning. The main goal of this research is to take advantage of fuzzy logic and build effective, adaptive approximator - a neuro-fuzzy system. The system was trained with use of samples that contain information about scattering characteristics and corresponding tuning screw deviations. Experiments were performed on four different filters which have 6 to 11 cavities. The results have been then compared with previous works which use artificial neural networks. The system learning phase has been proved to reach lower generalization and learning error.