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说明：  决策树(Decision Tree）是在已知各种情况发生概率的基础上，通过构成决策树来求取净现值的期望值大于等于零的概率，评价项目风险，判断其可行性的决策分析方法，是直观运用概率分析的一种图解法。由于这种决策分支画成图形很像一棵树的枝干，故称决策树。在机器学习中，决策树是一个预测模型，他代表的是对象属性与对象值之间的一种映射关系。Entropy = 系统的凌乱程度，使用算法ID3, C4.5和C5.0生成树算法使用熵。这一度量是基于信息学理论中熵的概念。 决策树是一种树形结构，其中每个内部节点表示一个属性上的测试，每个分支代表一个测试输出，每个叶节点代表一种类别。 分类树（决策树）是一种十分常用的分类方法。它是一种监督学习，所谓监督学习就是给定一堆样本，每个样本都有一组属性和一个类别，这些类别是事先确定的，那么通过学习得到一个分类器，这个分类器能够对新出现的对象给出正确的分类。这样的机器学习就被称之为监督学习。(Decision tree is a decision analysis method based on the known probability of occurrence of various situations, which can calculate the probability that the expected value of net present value is greater than or equal to zero, evaluate the project risk and judge its feasibility by constructing a decision tree. It is a graphic method of intuitively using probability analysis. Because this kind of decision branch is drawn as a graph, it is very similar to the branch of a tree, so it is called decision tree. In machine learning, decision tree is a prediction model, which represents a mapping relationship between object attributes and object values. Entropy = the disorder degree of the system, using algorithms ID3, C4.5 and C5.0, spanning tree algorithm using entropy. This measure is based on the concept of entropy in information theory.)

wav格式信号频谱分析，在matlab开发环境下可以很好的应用(wav format, the signal spectrum analysis, in the matlab development environment may be a good application of)

histogram equalization using MMBEBHE image processing

SDVS(a,k) test for matlabpool open local 8 Run in Xeon 8 cores

说明：  这是一个产生高斯随机信号的matlab源程序，可以做出统计直方图(Gaussian random signals generated source code matlab)

指纹图像特征提取，采用matlab编程实现(Fingerprint image feature extraction, using matlab programming)

四进制通信系统的进行蒙特卡罗仿真程序，以正交信号为基础。当均值分别等于０，０.１，１.０，２．０时完成１００００个比特的仿真并求出误差概率。绘出理论误码率和蒙特拉罗仿真的差错率并进行比较这俩个结果，并绘出每个均值情况下判决器的１０００个接受信噪比抽样(Four-band communication system to carry out Monte-Carlo simulation procedures to orthogonal signal basis. When the mean, respectively, equivalent to 10,000 completed 0,0.1,1.0,2.0 bit error probability simulation and obtained. Mapping theory and蒙特拉罗BER simulation这俩error rate and compare results, and the mean circumstances of each mapped)

Optics Caracters Reconogintion

小波包分析提取振动信号中的特征频率，模拟数据分析处理的过程，用于信号特征提取、信号消噪。( Wavelet packet analysis to extract vibration signal characteristic frequency, Analog data analysis processing, For feature extraction, signal de-noising.)

GABOR滤波器的设计程序.两个程序，都是基于matlab实现。(GABOR filter design process. The two procedures are based on matlab to achieve.)