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支持向量机SVM和核函数的matlab程序集(SVM matlab)

简单的阐述方式，可使读者尽快掌握要领。主要介绍了一些编程语句的使用方法。(A simple exposition of way, will enable readers to quickly grasp the essentials.It introduces a number of programming statements used.)

石头、剪子、布小游戏的MATLAB实现 希望对大家有帮助(shitou jianzi bu)

建模与估计参考教材它涉及系统辨识、状态估计、时间序列分析、多传感器信息融合四门学科及它们相互交叉、相互渗透的边缘学科和领域。(Modeling and estimation)

FLD的另一种求法，不用数值法解方程了，可以直接画出右半部分(FLD method for finding another, without the numerical method of solving equations, and can draw the right part)

Matlab - DC-Shunt Generator

lucas kanade optical flow detection-segmentation-

主要讲述小波理论分析,并对各章给出matlab仿真分析(Focuses on the analysis of wavelet theory, and gives the matlab simulation analysis)

用于多径直扩信号的仿真程序，对于研究直扩信号的人很有帮助。(Simulation program for multi-straight SS signals for the DS signal is helpful.)

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.)