ComputerAided Tuning of Cavity Filters Using Kernel Machine Learning

FONT face; Verdana; ZHOU Jin; ZHANG Fu; HUANG Jin; TANG Bo; XIONG Chang; FONT

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ComputerAided Tuning of Cavity Filters Using Kernel Machine Learning

更新时间：2025-07-16

- ComputerAided Tuning of Cavity Filters Using Kernel Machine Learning
- Acta Electronica Sinica Vol. 38, Issue 6, Pages: 1274-1279(2010)
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- Published：2010
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FONT face, Verdana, ZHOU Jin, et al. ComputerAided Tuning of Cavity Filters Using Kernel Machine Learning[J]. Acta Electronica Sinica, 2010, 38(6): 1274-1279.
DOI：

FONT face, Verdana, ZHOU Jin, et al. ComputerAided Tuning of Cavity Filters Using Kernel Machine Learning[J]. Acta Electronica Sinica, 2010, 38(6): 1274-1279. DOI：

摘要

<FONT face=Verdana>研究了一种基于核机器学习的腔体滤波器辅助调试方法.该方法根据工程中的调试经验数据，首先使用核机器学习算法建立了螺栓调整量和滤波器电性能之间的影响关系模型.然后应用此模型，使用优化技术构建了滤波器的辅助调整方法.实际滤波器的实验结果表明了该方法的有效性.该方法比较适用于工程中批量生产的腔体滤波器的辅助调试.

Abstract

<FONT face=Verdana>A computeraided tuning method based on machine learning is proposed in the paper.In the method

an effect model that reveals the relationships between the tunable screws and filter electrical performance is firstly developed by using a kernel algorithm

according to the data sets from tuning experience of technician.Then

a tuning procedure of filters is constructed by using the developed machine learning model.Finally

some experiments are carried out

and the experimental results confirm the effectiveness of the method.The approach is particularly suited to the computeraided tuning of volumeproducing filters.

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