红外与毫米波学报2024，Vol.43Issue(4)：490-496,7.DOI:10.11972/j.issn.1001-9014.2024.04.008
主成分分析及聚类方法在碲镉汞晶片参数判别中的应用研究
Application of principal component analysis and clustering methods in the discrimination of parameters in HgCdTe crystals
摘要
Abstract
A method for selecting parameters in HgCdTe crystals has been proposed,utilizing Principal Component Analysis(PCA)and clustering methods,with the establishment of a data model for screening the parameters of HgCdTe crystals.Within the model,the initial crystal data undergoes a cleaning and analysis process.PCA is employed for dimensionality reduction,and the Density-Based Spatial Clustering of Applications with Noise(DBSCAN)algo-rithm is used to identify the densest regions within the crystal data.Furthermore,the high-performance chip data,ob-tained after post-processing,is utilized to fit boundary ellipses for high-quality HgCdTe crystal parameters.These ellips-es act as criteria for identifying high-quality crystals.The model is capable of generating crystal ratings based on input electrical and optical parameters with a coverage rate exceeding 90%.关键词
碲镉汞/晶片筛选/主成分分析/聚类Key words
HgCdTe/crystal parameter selection/principal component analysis/clustering analysis分类
数理科学引用本文复制引用
吴佳昊,乔辉,李向阳..主成分分析及聚类方法在碲镉汞晶片参数判别中的应用研究[J].红外与毫米波学报,2024,43(4):490-496,7.基金项目
国家自然科学基金重点项目(42330110) Supported by the State Key Program of National Natural Science of China(42330110) （42330110）
