clustering

说明：  BAM是一种两层的异联想，内容可寻址存储器组成的反馈网络。 分类：离散，连续 和自适应BAM等。 1987年和1988年由Kosko提出的BAM型。 网络运行是双向的。对网络的一端输入信号，则可在另一端得到输出，该输出又反馈回来，经过多次反复，直到网络达到稳态为止(BAM is a two-tier Heteroassociation, content addressable memory component of the feedback network. Classification : discrete, continuous and adaptive BAM other. In 1987 and 1988 by the BAM Kosko type. The operation of the network is a two-way. The network side input signal can be received at the other end output, the output feedback to come back again, repeatedly, until the network reached so far Steady)

genetic algorithm for resource leveling, considering the job aveliable and the code is start time. matlab resource code, good reference.(resource leveling genetic algorithm,single resource)

implementing histogram equalization for image enhancement

说明：  使用MATLAB编程软件，编程实现在给定的话务模型下计算各个接口的消息总流量和带宽的用户界面； 使用MATLAB编程软件，编程实现在给定话务模型下各个接口之间的信令链路及所需要的中继端口数的用户界面； (Using MATLAB programming software, programming to achieve a given traffic model calculated all the news of the total interface bandwidth traffic and user interface using MATLAB programming software, programming to achieve in a given traffic model between the various interfaces signaling link and the need to relay port number of the user interface )

compressive sensing:Bayesian Compressive Sensing

source panel method matlab code for cylinder

QPSK signal matlab code

基于snell定律的射线追踪，与一般算法不一样，精度比较高(Based on Snell s Law ray tracing, and the general algorithms are not the same, relatively high accuracy)

mazen.o.hasna的五篇关于无线中继的文章 比较适合刚接触无线中继的学生 其中还有自己做的matlab仿真程序 只能做出大部分 小部分还是有问题 (mazen.o.hasna of five articles on wireless repeater is suitable for students who are new to wireless relay which also do their own matlab simulation program can only make the most of the small part of the problem is still there)

一个非常好用的国外牛人写的kalman滤波程序，(kfdemo.m is a Matlab script file to run a demonstration of the Bayesian Kalman filter. It loads file kfdemo.mat (saved as version 4 so that it will read in either v4 or v5 Matlab).The other files are called by kf.m (the Kalman filter) or included as they may be useful. Normalis.m normalises data to zero-mean, unit variance along components. I always do this before any further analysis.)