DVHOP

C. Torrence博士在分析厄尔尼诺现象时的示例程序，包含小波的重构部分，非常经典，该文被引用超过2400次(C. Torrence Dr El Nino phenomenon in the analysis of the sample program, including reconstruction of part of the wavelet, very classic, the paper cited more than 2400 times)

使用MATLAB用模式识别中的k聚类的方法进行分类，提供源程序，有图示(Pattern Recognition using MATLAB with the k-clustering approach to classification, to provide source code, there are icons)

3D algorithm for thinning in matlab

Markovian_model_for_Opportunistic_Request_Routing-maste的matlabr例程，同时还有相关的论文。《Analyzing Opportunisitic Request Routing in Wireless Cache Networks》(A simulation of Markovian_model_for_Opportunistic_Request_Routing based on matlab)

短时能量估计以及过零率估计，对声音信号的处理很有帮助，希望对大家有所帮助。(Short-term energy estimates and zero crossing rate is estimated that the processing of sound signals is helpful, we hope to help.)

matlab lectuers to program polyfitting

编写M文件，创建如下图形窗口，分别绘制如下图所示的曲线。 （1）曲线y=sin(t)sin(9t)，要求采用红色，点线。横坐标取值范围[0~ ]，标注x轴、y轴并加标题。 （2）一组余弦曲线，其振幅分别为0.4，0.6和0.8。横坐标取值范围[0~2 ]。添加图例与标题。进入图形编辑状态，调整图例的位置。 （3）分别绘制peaks函数的曲面图和网格线图。对曲面图做平滑处理，并添加标题与colorbar。 (Write M file, create the following graphics window, curves were plotted as shown below. (A) the curve y = sin (t) sin (9t), require the use of a red dotted line. The abscissa in the range [0 ~  ], labeled x-axis, y-axis and a title. (2) a set of a cosine curve, and the amplitude was 0.4, 0.6, 0.8. Abscissa value range [0 ~ 2  ]. Add a legend and title. Into the graphical editing mode, adjust the position of the legend. (3) were drawn surface chart peaks function and grid line graph. Surface charts do for smoothing and add titles and colorbar.)

说明：  对信号进行EMD分解后画出信号的希尔伯特包络谱程序，自己编写的，调试成功(EMD decomposition of the signal after the draw of the Hilbert envelope of the signal spectrum of procedures, I have written, debugging success)

matlb code for calculation of BER of ofdm with Qpsk

In numerical linear algebra, the Gauss–Seidel method, also known as the Liebmann method or the method of successive displacement, is an iterative method used to solve a linear system of equations. It is named after the German mathematicians Carl Friedrich Gauss and Philipp Ludwig von Seidel, and is similar to the Jacobi method. Though it can be applied to any matrix with non-zero elements on the diagonals, convergence is guaranteed if the matrix is either diagonally dominant, or symmetric and positive definite.