GApower

基于支持回归向量机的端点延拓程序解决EMD端点效应，包括向左延拓和向后延拓。(EMD solve end effect based on support vector machine regression endpoint extension programs, including the left rear extension and extension.)

图像的颜色特征提取，通过选择合适的阈值，将对象从复杂背景中提取出来(Image color feature extraction, by selecting the appropriate threshold, the object is extracted from complex background)

channel impulse response for CM4 testing code

算法,用蒙特卡洛法实现对排队等待问题的计算机模拟。(mathlab program)

多个光伏电池组合，可模拟光伏电池并网组合(Combination of multiple photovoltaic cells, photovoltaic cells can be simulated and network combination)

连续隐马尔可夫识别程序。 包含的模块，可以比较完整地进行语言识别。 主要模块： Test.m Train.m viterbi.m baum.m pdf.m recog.m mixture.m mfcc.m (speech recognize using HMM include 11 matlab fuction: Test.m Train.m viterbi.m baum.m pdf.m recog.m mixture.m mfcc.m )

he files in this package comprise the Matlab implementation of a foreground segmentation algorithm based upon graph cuts, described in: Better Foreground Segmentation Through Graph Cuts, N. Howe & A. Deschamps. Tech report, http://arxiv.org/abs/cs.CV/0401017. The file extractForeground.m contains a sample function that will perform a complete foreground segmentation for static camera video. It uses a number of parameters, which are described in the documentation. An attempt was made to choose sensible default values, but they may need to be adjusted for some videos. More generally, the implementation in extractForeground.m is only a suggestion of how the graph-based segmentation might be used. The same approach can be applied with other (perhaps time-adaptive) background models. The key step is at line 113 of the code, once the deviation array has been created. The graph-cut segmentation can be applied similarly to a deviation matrix computed in any other way.

这是一个求信号DEMON谱也就是包络谱的小程序， 信号是myfunction，DEMON.m里调用了这个函数( U8FD9 u162F u4E3 u4E3 u4E3 u6C2 u6C2 U8C03 u7528 u4E86 u8FD9 u4E2A u51FD u6570)

算术编码，matlab实现编码与译码，而且不考虑其精度(Arithmetic coding, matlab coding and decoding achieve, and do not take into account their accuracy)

说明：  对原始图像添加高斯噪声，并用邻域平均和中值滤波法进行滤波，并可以进行对比。(Gaussian noise added to the original image, and use neighborhood average and median filtering method for filtering, and can be compared.)