Modeling the effect of manufacturing precision on electrical performance of filters using support vector regression

Abstract

This paper presents a data-driven modeling method for cavity filters. In the method, according to the data set from the manufacturing of filters, a model that reveals the effect of manufacturing precision on electrical performance of cavity filters is firstly developed by linear programming support vector regression. Moreover, to solve the modeling problem of small data set, multi-kernel and prior knowledge are utilized to modify the traditional linear programming support vector regression. Finally, some experiments are carried out, and the experimental results confirm the effectiveness of the modified arithmetic and the modeling method for cavity filter. The model is particularly suited to the computer-aided manufacturing and automatic tuning system of volume-producing filters.