sapf1

How to create a modulated 64-QAM signal

matlab界面编程，详细的实例说明，可以给学习界面编程提供很好的帮助(matlab GUI)

实现了两步相移的基于随机相位掩码的图像加密和解密(To achieve a two-step phase shift mask image based on random phase encryption and decryption)

粒子群算法，matlab实现，包含注释，适合新手(Particle swarm optimization, matlab implementation, including annotations, suitable for novice)

一个HMM的Matlab实现方法，可实现孤立词语音识别(The Matlab realize a HMM method can realize an isolated word speech recognition)

Matlab Biased toolbox

迭代学习控制的MATLAB语言程序，实现迭代开控制。反复迭代30次，设置步长(Iterative Learning Control of the MATLAB language program, to achieve iterative open control. Iteratively 30 times, set the step size)

基于全局误差的BP神经网络辨识的MATLAB仿真程序，代码有注释(Based on global error of BP neural network identification MATLAB simulation program, code annotated)

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.)

SHA tests are configured for BYTE oriented implementations for Andriod.