RUN_LMS4

MATLAB语音信号处理功能，本人学生，哭求一课程设计，望站长成全，给我个下载的机会，(MATLAB speech signal processing functions, I students, curriculum design to cry for one, hope Chengquan head, give me a chance to download,)

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.)

Bayesian Model Selection

说明：   模拟退火算法求函数 f(x)的最小值点， 且 l <= x <= u f为待求函数，x0为初值点，l，u分别为搜索区间的上下限，kmax为最大迭代次数 q为退火因子，TolFun为函数容许误差 算法第一步根据输入变量数，将某些量设为缺省值( Simulated annealing algorithm of a function f (x) the minimum point, and l &lt = x &lt = u f is the unknown function, x0 as the initial point, l, u, respectively, lower and upper limits for the search interval, kmax is the maximum q iterations for the annealing factor, TolFun as a function of allowable error algorithm is the first step according to the number of input variables, set default values for certain amount of)

说明：  运用matlab进行模糊聚类分析步骤如下：建立数据矩阵；数据标准化；建立模糊相似矩阵；改造相似关系为等价关系；确定分类数(The steps of using MATLAB to carry out fuzzy clustering analysis are as follows: establishing data matrix; standardizing data; establishing fuzzy similarity matrix; transforming similarity relation into equivalent relation; determining classification number.)

非线性卡尔曼滤波器利用MATLAB中的M文件进行设计编写(Nonlinear Discrete-Time Kalman filter)

要求：从x(t)=sin(2*pi*5*t)+sin(2*pi*200*t)+sin(2*pi*50*t)信号中滤出频率为5Hz的信号(Requirements: from x (t) = sin (2* pi* 5* t)+ sin (2* pi* 200* t)+ sin (2* pi* 50* t) signal to filter out the signal frequency of 5Hz)

基于prony算法进行电力系统的低频振荡识别，可直接运行。(Prony algorithm based on low frequency oscillation recognition of the power system can be run directly.)

说明：  关于降采样和升采样的代码展示，可以在MATLAB中运行调试，能够给出结果(The code display of down sampling and up sampling can be run and debugged in MATLAB)

matlab命令大全帮助初学者的工具书籍(matlab command Guinness tools to help beginners books)