Feature selection is an important process in a target classification program and directly affects the design and performance of the classifier.
特征选择是目标分类的一项重要步骤，直接影响到分类器的设计和性能。
The techniques of feature extraction, feature selection and design of classifier for passive sonar target recognition are reviewed.
文章对被动声纳目标识别的特征提取、特征选择和分类器设计方面进行了回顾。
This thesis studies the feature selection method of HRRP and proposes a RATR method in target subspace based on the analysis of noise-match in HRRP space.
基于对HRRP空间雷达自动目标识别中冗余噪声匹配的分析，研究了高分辨距离像的特征选择方法，提出了一种基于目标子空间的雷达自动目标识别方法。
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