shiermaibo2

一美国佬编的经典MUSIC算法，基于线列阵，算法简单易懂，初学好用(classic MUSIC Algorithm from american ULA)

基于合成孔径雷达sar单站式的成像仿真BP算法(Monostatic SAR imaging simulation rd algorithm )

说明：  半监督学习matlab代码程序，训练集 测试集代码，优化半监督svm 朴素贝叶斯 等等(matlab code program, training set test set code, optimized semi-supervised svm naive Bayes, etc.)

本程序为《自适应信号处理》（王永德等译，机械工业出版社）书中107图SER算法和LMS算法比较的源程序，仿真效果和书上一致(This program is " adaptive signal processing" (s Acoustic other translation, Mechanical Industry Press) book 107 SER algorithm and LMS algorithm for graph comparison of the source, the simulation results and the same book)

Reactor Calculator Assume: Batched, 100 conversion

用于计算二维稳态热传导方程的隐式算法程序(Two-dimensional steady-state heat conduction equation implicit algorithm procedures)

Modelling and Control of a Three-Phase Four-Switch PWM-VSR in d-q Synchronous Frame

说明：  Matlab,图像识别，计算图像中物体的个数。测试图片读入图像程序图像识别计数主程序 (objectrecog)

speed control of brushless dc moter

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.)