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svd提取特征脸，Computer Vision课程作业，用PCA计算特征脸，提取主成分，用PCA系数进行相似度计算。(comupute face similarity using eigenface and PCA analysis)

q713是低通滤波器及傅里叶变换时域卷积定理验证，q714是用符号工具箱解z变换问题(q713 is a low-pass filter and the Fourier transform time-domain convolution theorem verification, q714 is symbolic toolbox solution of the problem z transform)

这里实现了基于四种SVM工具箱的分类与回归算法: 1、工具箱：LS_SVMlab Classification_LS_SVMlab.m - 多类分类 Regression_LS_SVMlab.m - 函数拟合 2、工具箱：OSU_SVM3.00 Classification_OSU_SVM.m - 多类分类 3、工具箱：stprtoolsvm Classification_stprtool.m - 多类分类 4、工具箱：SVM_SteveGunn Classification_SVM_SteveGunn.m - 二类分类 Regression_SVM_SteveGunn.m - 函数拟合 更详细的相关函数说明请通过help命令查看！(Here the realization of the four SVM toolbox based on the classification and regression algorithm: 1, Toolbox: LS_SVMlabClassification_LS_SVMlab.m- Multiclass Classification Regression_LS_SVMlab.m- function fitting 2, the toolbox: OSU_SVM3.00Classification_OSU_SVM.m- Multiclass Classification 3, Toolbox: stprtoolsvmClassification_stprtool.m- Multiclass Classification 4 toolbox: SVM_SteveGunnClassification_SVM_SteveGunn.m- II Category Regression_SVM_SteveGunn.m- function fitting a more detailed explanation of the correlation function through the help command to view!)

In computer vision, the Lucas–Kanade method is a widely used differential method for optical flow estimation developed by Bruce D. Lucas and Takeo Kanade. It assumes that the flow is essentially constant in a local neighbourhood of the pixel under consideration, and solves the basic optical flow equations for all the pixels in that neighbourhood, by the least squares criterion.

这是一段自己编写的基于高斯模型的matlab人脸识别代码(This is a piece I have written matlab face recognition code based on the Gaussian model)

MATLAB入门视频，初学者可多学习，简单，直观，易懂(MATLAB Introduction to video, beginners can learn more than simple, intuitive, easy to understand)

流行学习英文文献，主要是局部线性嵌入方法的改进(Pop learning English literature, mainly locally linear embedding Improvement)

基于PWM调制的并网逆变器matlab仿真模型(matlab model)

说明：  《matlab使用详解》的部分源码，希望对你有所帮助(err)

说明：  很好的多元回归分析源码，其中一部分是自己写的(Multiple regression analysis a good source, part of which is to write their own)