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基于核机器学习的腔体滤波器辅助调试 被引量：3

Computer-Aided Tuning of Cavity Filters Using Kernel Machine Learning
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摘要 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. 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.
作者 周金柱 张福顺 黄进 唐波 熊长武
机构地区 西安电子科技大学电子装备结构设计教育部重点实验室 西安电子科技大学天线与微波技术国家重点实验室 西南电子技术研究所
出处 《电子学报》 EI CAS CSCD 北大核心 2010年第6期1274-1279,共6页 Acta Electronica Sinica
基金 国家973重点基础研究发展规划(No.61358) 国家自然科学基金资助(No.50475171 10433020)
关键词 腔体滤波器 辅助调试 机器学习 螺栓 经验数据 cavity filters computer-aided tuning machine learning tunable screws tuning experience
分类号 TN713 [电子电信—电路与系统]
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参考文献20

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二级参考文献38

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共引文献30

同被引文献16

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电子学报
2010年 第6期

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