the8part

非常不错的书籍，《微粒群算法》供8章和2个附录，依次上传第3章绪论(Very good books, Particle Swarm Optimization for 8 chapters and two appendices, followed by From Chapter 3 Introduction)

使用K－均值聚类算法在IRIS数据上进行聚类分析.(K-means clustering algorithm using IRIS data in the cluster analysis.)

多假设跟踪Matlab代码例子,也是从别的地方下载的(example of MHT target tracking)

说明：  用多层前向网络的BP算法拟合函数 说明：1）网络结构为三层（输入层、1个隐层和输出层）； 2）获取两组数据，一组作为训练集，一组作为测试集； 3）用训练集训练网络； 4）用测试集检验训练结果。(Fitting the function with BP algorithm of multilayer forward network)

Td-scdma system level simulation platform of mobile communication system, can generate simulation framework

由于卫星与用户接收机二者的连线方向上存在相对运动，因此引起了载波和伪码的多普勒效应，再加上接收机晶体震荡频率漂移和卫星时钟频漂等原因。接收机实际接收到的卫星载波中心频率一般不再等于信号被发射时的标称频率，这就需要接收机在载波频率一维对信号进行搜索。同时，由于卫星到接收机的距离时刻变化，加上接收机始终相对于GPS时间的偏差又并不固定，因而接收信号的伪码相位值也在改变，所以接收机也要在码相位一维对信号进行搜索。扩频信号的捕获是一个对目标信号频率域和相位域进行的二维搜索过程。(Because of the relative motion between the two of the satellite and the user receiver, the Doppler effect of the carrier and pseudo-code is caused, and the frequency drift of the oscillation of the receiver crystal and the frequency drift of the satellite clock are added. The frequency of the satellite carrier center that the receiver actually receives is generally no longer equal to the nominal frequency of the signal being transmitted, which requires the receiver to search the signal in one dimension of the carrier frequency. At the same time, because the distance between the satellite to the receiver is changed, the deviation of the receiver always relative to the GPS time is not fixed, so the pseudo code phase value of the received signal is also changing, so the receiver also searches for the signal in the code phase. The acquisition of spread spectrum signal is a two-dimensional search process for the frequency domain and phase domain of the target signal)

Finite element method programming Matlab

有关于滑模变结构的S函数的例程2，用来学习S函数结构(About SMVSC S-function routines 2, S-function structure for learning)

典型混沌序列的生成，可以根据自己的参数修改，并进行相空间重构(A typical chaotic sequence is generated, you can modify according to their parameters, and phase space reconstruction)

The ultimate goal of the project is to develop a smart autonomous robot that is able to navigate fully utonomously around the laboratory floor or even the campus