twenty_four

本文件包含了William Stallings编写的优秀教材Data and Computer communications的中文影印版，以及书中的课后习题答案(This document contains the William Stallings excellent teaching materials prepared by Data and Computer communications photocopy version of the Chinese, as well as after-school book answer Exercises)

说明：  mte代码，wsn经典算法。画三维图的具体代码。(Mte code, WSN classical algorithms. Three-dimensional graph concrete code painting. )

说明：  图像处理基础算法源代码，此文件含有大多数代码的合集(Image processing algorithms based on source code, this file contains most of the code collection)

用matlab写的单模光纤的LP01模场分布仿真(LP01 mode field distribution simulation matlab write single-mode fiber)

让ARToolKit支持MQO模型所需的所有函数实现代码，均在对应的GLMetaseq.c中。(Let ARToolKit supports all the functions needed to MQO model codes, both in the corresponding GLMetaseq.c.)

岩石物理模型建模的另一种方法，同样可以翻译弹性参数与物性参数间的关系。(Another method of rock physics modeling, the same can translation parameters and physical parameters of elastic)

说明：  6.78M class e 无线充电仿真(6.78M class e wireless charging simulation)

说明：  MATLAB在图形窗口中绘制或输出图形，MATLAB to draw in the graphics window or output graphics(MATLAB to draw in the graphics window or output graphics)

Goertzel algorithm in matlab

马氏距离是一种有效地计算两个样本集之间相似度的算法（数据之间协方差距离），与欧式距离相比，它考虑了各种特征之间的联系。本实验旨在通过给出的样本数据，设计一个最小马氏距离分类器并对测试点进行分类，然后将其与最小欧式距离分类器进行比较，实验得出当协方差矩阵为单位阵时，最小马氏距离分类器将与最小欧式距离分类器等价。本实验还根据实验样本设计贝叶斯分类器进行分类，并与最小马氏距离分类器进行比较，比较两种分类器的分类效果。(Markov distance is an effective method to compute the similarity between the two samples (data covariance distance), compared with the Euclidean distance, which takes into account the link between different characteristics. This experiment aimed at through the given sample data, design a minimum Mahalanobis distance classifier and classify the test points, and then compare it with the minimum Euclidean distance classifier. Experimental results showed that when the covariance matrix is a unit matrix, minimum Mahalanobis distance classifier with the minimum Euclidean distance classifier equivalent.In this experiment, according to the experimental design of the Bias classifier, and compared with the minimum distance classifier, the classification results of the two classifiers are compared.)