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刚刚来这，新手没什么资源，就把书籍配套的用于信号处理的几个matlab例子发给大家，应该能有用！(Just come to this, no new resources to put books for signal processing supporting several examples matlab distributed to Members should be able to be useful!)

用matlab识现人脸表情识别的方法，对于初学者matlab以及研究人脸表情识别有很大的帮助(Matlab knowledge with Facial Expression Recognition is the way to matlab for beginners as well as facial expression recognition is very useful to)

输入训练样本集和测试样本集，通过提取HOG然后用SVM实现分类。(Input training samples and test samples, extract HOG and implement classification with SVM.)

说明：  超声图像重建，包括基本步骤和一部分源代码。可用作实验设计。(Ultrasound image reconstruction)

zernike矩需要用到的一些处理函数，可以直接调用，非常方便(zernike moments need to use some of the processing function can be called directly is very convenient)

全变差图像处理Matlab程序，for the paper: "Algorithms and Software for Total Variation Image Reconstruction via First-Order Methods, Numerical Algorithms"(Software for Total Variation Image Reconstruction (for Matlab Version 7.5 or later) "mxTV" is a software package for image reconstruction based on the Total Variation model, and including denoising, inpainting, and deblurring. The work was carried out as part of the project CSI: Computational Science in Imaging, funded by the Danish Research Council for Technology and Production Sciences, and headed by Prof. Per Christian Hansen, DTU Informatics. The collaborators are DTU Informatics, Dept. of Electronic Systems at Aalborg University, and MOSEK ApS. The underlying algorithms are based on recently published first-order methods developed by Nesterov, tailored specifically to the image restoration problems. These methods have O(1/ε) complexity, where ε is the accuracy of the solution. The core computational routines are written in C, with a mex interface to Matlab. The algorithms and the software are described in the paper: J. Dahl, P. C. Hansen, S. H. Jensen, and T. L. Jensen, Alg)

用格拉布斯坏值提出理论于剔除统计样本样本中坏值，将好值和坏值分开(used to delete the bad data for statistic based on the Grubs theory)

matlab的svm神经网络文件，可用于风速预测，能够生成预测图(the rbf neural network matlab files, can be used for wind prediction, to generate prediction chart)

说明：  这里面包含两个程序段，是学习SIMULINK的基础程序，很有借鉴意义，不学习的就不要浪费时间了(This procedure consists of two paragraphs which is the basis of SIMULINK learning process, referential significance, not to learn not to waste time on)

The Gauss-Seidel technique is intuitive and easy to use on large or small problems. However, you should beware that the convergence tolerance must be carefully selected. Because the convergence criterion is based on the error between iterations, the same convergence criteria may lead to very different results. The direct solution technique presented in Section 2.6.2 is generally preferred over an iterative technique like Gauss-Seidel iteration if a tool such as MATLAB that provides a computationally efficient means of solving sparse matrices is available.