fdec2bin_diy

Gerald Teschl s matlab files for german book: "Mathematik für Informatiker 1: Diskrete Mathematik und lineare Algebra" ISBN "9783540774310"

说明：  On Maximum-Likelihood Detection and the Search for the Closest Lattice Point

根据目标RCS起伏的特征给出相应的检测概率计算方法。书中常用的办法(According to the characteristics of the fluctuation of the target RCS, the corresponding detection probability calculation method is given. Common methods in books)

轻武器权限申请程序等外侧段v二大王我我的2的1我(In cognitive radio networks, power control is considered as an important issue to improve the performance of dynamic spectrum sharing. In this paper, in order to maximize the efficiency of the system, the secondary users and primary user behaviors will be considered. )

改程序是用MATLAB写的有关运动背景补偿的算法(Reform program is about the background motion compensation written using MATLAB algorithm)

convolution and deconvolution program usin matlab

对于复杂网络中各种节点的分布进行计算和求证时不是幂律分布，并求出相关的指数。(Power-law distribution of complex networks)

Kalman filter examples

实现模糊聚类分割的一些方法，以及一些编程代码供学习和复习。(To achieve some of the methods of fuzzy clustering segmentation)

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.)