基于SVD算法求解三维点集匹配的Matlab代码（带详细注释）

矩阵分的奇异值分解 国内的线性代数书籍都只讲了对称矩阵的分解，没有一般矩阵的分解 对图形学很有用

The topic of this article, the singular value decomposition, is one that should be a part of the standard mathematics undergraduate curriculum but all too often slips between the cracks. Besides being rather intuitive, these decompositions are incredibly useful. For instance, Netflix, the online movie rental company, is currently offering a $1 million prize for anyone who can improve the accuracy of its movie recommendation system by 10%. Surprisingly, this seemingly modest problem turns out to be quite challenging, and the groups involved are now using rather sophisticated techniques. At the heart of all of them is the singular value decomposition. A singular value decomposition provides a convenient way for breaking a matrix, which perhaps contains some data we are interested in, into simpler, meaningful pieces. In this article, we will offer a geometric explanation of singular value decompositions and look at some of the applications of them.

图像模式识别svd（奇异值分解）算法及图像相似度计算delphi源代码.

尝试使用GPU加速随机化的SVD。 已针对目前的顶级算法进行了测试。 / nbs-

【图像加密】基于DCT(离散余弦变换)与SVD(奇异值分解)域自适应嵌入水印matlab源码.zip

基于奇异值分解的手写体识别，仅用于学习交流，请勿用于商业用途和其他用途。如需用于非学习交流用途，请先私信联系我。

SVD 奇异值分解代码，矩阵分析的利器，可以高精度的分解各种类型的矩阵

本文第一部分对SVD进行了简单的介绍，给出了定义和奇异值分解定理；第二部分简要地列举了SVD的应用；第三部分则构造和分析了各种求解SVD的算法，特别对传统QR迭代算法和零位移QR迭代算法进行了详细完整的分析；第四部分给出了复矩阵时的处理办法；第五部分是对各种算法的一个简要的总结。

Elad2006年的论文以及论文的实现代码