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主成分分析中特征根等输出,输入变量可选择最大迭代次数-principal component analysis, and other characteristics of the output - input variables can choose the largest number of iterations
Update : 2008-10-13 Size : 1.44kb Publisher : 李楠

人脸识别的源程序,用Matlab语言实现,可以参考看一下。
Update : 2008-10-13 Size : 785byte Publisher : 李金

DL : 0
主成分分析中特征根等输出,输入变量可选择最大迭代次数-principal component analysis, and other characteristics of the output- input variables can choose the largest number of iterations
Update : 2025-02-19 Size : 1kb Publisher : 李楠

人脸识别的源程序,用Matlab语言实现,可以参考看一下。-Face recognition source code, using Matlab language, can refer to a look.
Update : 2025-02-19 Size : 1kb Publisher : 李金

PCA方法实现人脸识别,输出数据库中最象的前两人-PCA method for face recognition, the output database of the most as the first two
Update : 2025-02-19 Size : 5kb Publisher : 王华

PCA算法在matlab中的实现,简单有效-PCA algorithm implementation in matlab, simple and effective
Update : 2025-02-19 Size : 1kb Publisher : 张其

DL : 0
读入一组bmp格式的图像,进行PCA,主成分分析,用于人脸识别系统等-Read a set of bmp format images, the principal component analysis
Update : 2025-02-19 Size : 3kb Publisher : 木木

pca程序,PCA可以用于图像处理等方面-pca procedure
Update : 2025-02-19 Size : 179kb Publisher : liumeihong

DL : 0
principal component analysis (PCA ) is a well known approach for dimensionality reduction of the feature space. It has been successfully applied in face recognition. The main idea is to decompose face images into a small set of feature images called eigenfaces, which can be considered as points in a linear subspace called “face space” or “eigenspace”
Update : 2025-02-19 Size : 2kb Publisher : omid

主元分析,主要用于多维数据的降维处理,能够从多维数据中提取出最主要的元素,从线性变换的角度来说就是坐标表换到一个能够体现系统特征的基座标系上-Principal component analysis, multidimensional data is mainly used for dimension reduction process, multi-dimensional data can be extracted from the most important elements, from the point of view is the linear transformation of coordinates for the system to reflect the characteristics of a standard system on the base
Update : 2025-02-19 Size : 1kb Publisher : 张贲

matlab下实现的pca降维算法,降低数据维数,保留数据的主特征-pca dimensionality reduction algorithm on matlab
Update : 2025-02-19 Size : 1kb Publisher : fanlongfei

DL : 0
自己写的pca matlab 程序,简单,识别率高,可运行-PCA matlab program to write their own simple, high recognition rate, you can run
Update : 2025-02-19 Size : 1kb Publisher : ph

pca 人脸识别算法,主成分分析 ( Principal Component Analysis , PCA )是一种掌握事物主要矛盾的统计分析方法,它可以从多元事物中解析出主要影响因素,揭示事物的本质,简化复杂的问题。计算主成分的目的是将高维数据投影到较低维空间.-pac faces dectect for matlab
Update : 2025-02-19 Size : 2.74mb Publisher : weijisheng

DL : 0
让初学者可以更加容易了解PCA算法的基本运行过程-For beginners can more easily understand the basic operation process of PCA algorithm
Update : 2025-02-19 Size : 1kb Publisher : 呼呼

DL : 0
matlab 运用PCA算法对图像降维级图像重建代码-matlab image using PCA dimensionality reduction algorithm for image reconstruction code level
Update : 2025-02-19 Size : 10kb Publisher : 吴亮

DL : 0
在matlab上实现数据PCA处理,可以实现不同阶数的图像显示,-PCA processing data on matlab, can achieve image display different orders,
Update : 2025-02-19 Size : 85kb Publisher : zhang

DL : 0
基于Python在Swiss roll上实现PCA,并应用LE算法进行改进。-Python implementation PCA on the Swiss roll, and apply the LE algorithm based on improved.
Update : 2025-02-19 Size : 1kb Publisher : 刘蕾

DL : 0
PCA主成分分析源程序,可以运行,简单易懂,MATLAB(PCA principal component analysis source program, can run, easy to understand, MATLAB)
Update : 2025-02-19 Size : 1kb Publisher : 啥子64151465
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