PaintFlagsDrawFilterTest

这个源码可以分析绘制多种信号的模糊函数，已经试验过巴克码，线性调频信号，脉冲信号等(Description: This program estimates and plots the ambiguity function for any signals. I have tested it for the Barker code, chirp signal, pulse signal. for good results the length of the input vector (Ut)should be more than 7. Example- a rectangular pulse should be described as[1 1 1 1 1 1 1]. Please, give your suggestions. it is made with the help of "xcorr" function (Author: R. Losada) in MATLAB and Ilia Iliev from TU-Sofia )

turbo码的matlab仿真程序，仅供参考，希望对您有用(turbo codes matlab simulation program for information purposes only, hope useful to you)

Tikhonov正则化方法的一点注记,Tikhonov正则化方法的一点注记(Tikhonov regurlarization,Tikhonov正则化方法的一点注记)

Harris Corner Detector

A article about face Verification Using GaborWavelets and AdaBoost

此文件中有部分内容，对于初学MATLAB的人有帮助，前俩部分是一些MATLAB的基础操作，第三部分是线性方程数值解的雅克比迭代和高斯—赛德尔迭代的例子，第四部分是Gauss-Legendre积分公式，Newton-Cotes积分公式的俩个数值积分的例子，第五部分是Euler公式、向后Euler公式、改进Euler公式，二阶Runge-Kutta等方法（微分方程数值解）。(The first two parts are basic operations of MATLAB. The third part is examples of Jacobian iteration and Gauss-Seidel iteration of numerical solution of linear equation. The fourth part is examples of Gauss-Legendre integral formula and Newton-Cotes integral formula. The fifth part is Euler formula, backward Euler formula, improved Euler formula, second-order Runge-Kutta method (numerical solution of differential equation).)

单列多服务台排队系统 概要设计 首先根据系统初始化输入的数据对系统进行初始化，根据顾客的数量和顾客平均到达时间间隔，产生系统中每名顾客到达时间间隔，将每名顾客到达时刻插入事件表，事件表根据时间采用最小堆进行排序，最早发生的事件放到事件表的顶端。(Summary of single multi-server queuing system design is first initialize the input data according to the system to initialize the system, according to the number of customers and average customer arrival time, a system in the arrival time for each customer, each customer will get time into the event table, event table with the minimum heap according to the time to sort the events into the first event table top.)

在不同的调制方法下，信道容量的比较，利用matlab 编写的程序(the difference of the capacity under the difference way )

基于PCA 和BP 神经网络的人脸识别方法是针对 PCA 方法中存在的高维数问题和它对未训 练过的样本识别率低的缺点而提出的。该方法在预处理的基础上，利用粗糙集对 PCA 降维处理后的人脸特征进行约简，提取其中分类能力强的特征，实现在识别精度不变的情况下，有效的去除冗余信息；然后将约简后的属性输入到神经网络进行规则提取，利用神经网络非线性映射和并行处理的特点，增强对人脸图像识别的泛化能力。实验证明，使用该方法在识别率上有一定的提高(Face recognition method based on PCA and BP Neural Network)

在基带传输系统中将加网孔均衡与不加网孔均衡的结果作对比(In the base-band transmission system will increase mesh is balanced and not the result of a balanced mesh for comparison)