Feature value extraction is key technology in text processing, outstanding feature value could really embody the attribute of the text.
特征值提取是文本处理中的关键技术，优秀的特征值才能真正反映出文本的属性。
Classical feature extraction methods include: Principle Component Analysis, Singular Value Decomposition, Projection Pursuit, Self-Organizing Map, and so on.
传统的特征提取方法主要有：主分量分析、奇异值分解、投影追踪、自组织映射等。
The algebraic feature extraction of images and the authors' research work on singular value vectors as a kind of algebraic features of images are emphasized.
重点介绍了图像的代数特征抽取以及作者关于奇异值特征矢量作为图像的一种代数特征方面的研究工作。
This paper presented a new feature extraction according to the characteristics of display value of digital meters.
根据数字仪表字符的特点，提出一种新的特征提取方法。
Memories, Recognition, Feature Extraction, Dynamic protection, Self-regulation are the special mechanism of the immune system, which has good application value.
免疫系统的记忆功能、识别功能、特征提取功能、动态保护、自我调节功能等等，有着很好的应用价值。
A feature extraction method of high-range-resolution radar profiles, which takes advantage of wavelet packet transform and modified SVD (singular value decomposition) was proposed.
提出了基于小波包变换和改进奇异值分解的高分辨雷达目标一维距离像特征提取方法。
The average value of separability measure is as high as 91.7%, which indicates that this method is quite effective in the feature extraction of ultrasonic flaw echoes.
结果表明：该方法提取的缺陷回波信号特征值，其可分性测度均值达91.7%，从而证明该方法对超声检测缺陷回波信号的特征提取是相当有效的。
Computing method of weighted value for feature item based on text representation can determine extraction of text feature, which have influence on accuracy of the text clustering.
文本表示中特征项的权值计算方法决定了文本特征的提取，在很大程度上影响了文本聚类的准确率。
Symbiotic Matrix and feature extraction in the application for two or gray value image feature extraction.
共生矩阵及其在特征提取中的应用，用于灰度或二值图象的特征提取中。
Here, we use the singular value decomposition and principal component analysis for facial feature extraction, using the average distance category as discrimination on the basis of authentication.
其中人脸特征提取采用了奇异值分解和主分量分析法，身份验证则采用了以类内平均距离为判据的算法。
Here, we use the singular value decomposition and principal component analysis for facial feature extraction, using the average distance category as discrimination on the basis of authentication.
其中人脸特征提取采用了奇异值分解和主分量分析法，身份验证则采用了以类内平均距离为判据的算法。
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