搜索资源列表
gmeans
- gmeans-- Clustering with first variation and splitting 文本聚类算法Gmeans ,使用了3种相似度函数,cosine,euclidean ,KL.文本数据使用的是稀疏矩阵形式. -gmeans clustering with first variation and splitting Gmeans,a text clustering algorithm, uses 3 functions,cosine,euclidean and
BasedonKLTransformFaceIdentify
- 基于KL变化的人脑识别Matlab程序.
ClusterKLTransformation
- KL变换的实现，对连续六幅TM影像进行处理，算出前三个主要分量的图像
KL2
- 人脸识别：利用奇异值分解和KL变换的投影，是很有价值的一篇文章-Face Recognition : The Singular Value Decomposition and KL transform projection, it is valuable to an article
KL变换
- KL变换模式识别作业三 一、编程要求： 编程实现KL变换，并对TM六波段图像进行演算。 KL变换的思想是：从n维特征选取m维特征，删去的n-m维特征不一定就是无用的信息，如何在信息损失最小的情况下选取特征，在理论上就显得更严密些。通常采用正交变换，得到新的经变换的模式， 以保证信息损失最小情况下获得有利于分类的特征。 二、编程思想： 将6副图象依次输入获得灰度值存在一个6*size(size为一副图象的像素数)的二维数组中，计算每个波段的灰度均值，然后计算协方差矩阵，得出特征值
KL
- 数据挖掘中计算KL距离在matlab环境下的代码-KL distance calculations in data mining environment in matlab code
KL2
- 本程序利用K-L变换已经K-L变换的最优压缩，建立分类器，并选择投影方向，画出投影过后的效果-This procedure has been the use of KL transform KL transform optimal compression, the establishment of classifier, and choose the direction of projection, drawn after the effect of projection
2
- 基于肤色分割和KL变换的复杂背景的图像的人脸识别-Complex background based on color image segmentation for face recognition
faceidentify
- 用KL变换简单实现少数目人脸识别，附Sumlink仿真-KL transform with a simple implementation of a small number recognition, with a Sumlink simulation
LDA-Code
- 主要是LDA 包的程序 其中有KL，EM算法和一些推论-The program is mainly LDA package including KL, EM algorithm, and some inferences
KL
- matlab编写的K-L变换算法，实验数据为Iris，分类为BP算法，运行良好！-Matlab prepared by the KL transform algorithm, the experimental data for the Iris classified as BP algorithm, a good run!
s2
- 基于KL变换的特征提取 用KL变换进行模式识别 -KL transform pattern recognition based on KL transform feature extraction
KLTransform
- 本文档是对KL变化的解释，通过将KL变换和傅里叶变换的对比加深了对KL变换的理解-This document is a change in the interpretation of KL, by comparing the KL transform and Fourier transform deepened understanding of the KL transform
KL_SVD_face_recognition
- PCA主成分分析，采用KL投影和SVD分解提取人脸特征向量，最后采用最近邻判别法计算识别率。-Face recognition based on PCA. KL projection and SVD are used to extract face eigenvectors. Recognition rate is calculated by k nearest neighbors(KNN) method.
KL
- 基于KL变换的人脸识别技术,富有图片例子和程序说明-Face recognition based on KL transform technology, rich picture examples and procedures
xm_CPTDistanceCompare
- BN网络参数之间的KL距离 (Kullback–Leibler Distance) 计算，用于比较相似度-BN KL distance between network parameters calculation, used to compare similarity
2012011539_homework3
- 模式识别：神经网络算法使用，PCA和KL变换-Pattern recognition: neural network algorithm, PCA and KL transform
FlowwithoutPyramidLevels.py.tar
- a code KL optical flow between two images