shape-feature subspace 形状特征子空间
linear feature subspace 线性特征子空间
adaptive feature subspace 自适应特征子空间
classified feature-subspace 分类特征空间
subspace feature selection 子空间特征选择
Through analysis and constraint the conditions of feature subspace,the algorithm we proposed can obtain a high detection probability and security,a low false alarm probability.
通过对特征子空间选取限制,算法具有高的检测概率和安全性,低的虚警概率。
参考来源 - 一种基于空间优化的彩色图像鲁棒水印算法Then, the performance of two SVD algorithms and feature subspace radar target recognition algorithm based on SVD are evaluated according to real data of planes.
进而将两种SVD算法应用在特征子空间雷达目标一维距离像识别法中,使用实测数据对其进行速度验证和性能评估。
参考来源 - 基于DSP的雷达目标识别算法高速实现研究·2,447,543篇论文数据，部分数据来源于NoteExpress
The local feature based representation could be obtained by choosing suitable dimension of the feature subspace in NMF.
非负矩阵分解过程中，适当地选取特征空间的维数能够获得原始数据的局部特征。
Then, the performance of two SVD algorithms and feature subspace radar target recognition algorithm based on SVD are evaluated according to real data of planes.
进而将两种SVD算法应用在特征子空间雷达目标一维距离像识别法中，使用实测数据对其进行速度验证和性能评估。
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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