kaoxiang4

本文件包含了两个直扩和跳频的例子，用MATLAB语言实现，而且还包括例子的原文及大量注释，十分详细(This document contains two examples of DS and FH, with the MATLAB language, but also examples of the original and a lot of notes, very detailed)

this file is an imlementation of PII scheme of PAPR reduction for MCMs Scheme

OFDM载波同步算法的研究，验证后顺利运行，仿真效果好(After the OFDM carrier synchronization algorithm research, validation run smoothly, good simulation effect)

FRFT的测试程序,鉴定当前FRFT所使用阶次的合理性()

这是以上各个函数的作图程序，比较经典，可以控制你所画的图(This is a function of the mapping process above all, more classic, you can control the drawing)

MN逻辑法用于航迹起始，演示程序包括杂波环境下，整个跟踪全过程(MNlogic Track start Target Tracking)

聚类算法，不是分类算法。分类算法是给一个数据，然后判断这个数据属于已分好的类中的具体哪一类。聚类算法是给一大堆原始数据，然后通过算法将其中具有相似特征的数据聚为一类。这里的k-means聚类，是事先给出原始数据所含的类数，然后将含有相似特征的数据聚为一个类中。所有资料中还是Andrew Ng介绍的明白。首先给出原始数据{x1,x2,...,xn}，这些数据没有被标记的。初始化k个随机数据u1,u2,...,uk。这些xn和uk都是向量。根据下面两个公式迭代就能求出最终所有的u,这些u就是最终所有类的中心位置。(Clustering algorithm, not a classification algorithm. Classification algorithm is to give a figure, and then determine the data belonging to a specific class of good which category. Clustering algorithm is to give a lot of raw data, and then through the algorithm which has similar characteristics data together as a class. Here k-means clustering, is given in advance the number of classes contained in the raw data, then the data contain similar characteristics together as a class. All information presented in or Andrew Ng understand. Firstly, raw data {x1, x2, ..., xn}, the data is not labeled. K random initialization data u1, u2, ..., uk. These are the vectors xn and uk. According to the following two formulas can be obtained final iteration all u, u is the ultimate all these classes the center position.)

frft用于线性调频信号多普勒调频率估计(frft transform for doppler frequency rate estimation)

一篇讲解FDTD中，隐式格式迭代，总场散射场分离的改进的论文，对于学习总场散射场有重要作用。(FDTD in a brief, implicit iteration, the total field scattered field improved separation of papers, total field scattered field for the study has an important role.)

单位冲击响应 单位脉冲响应 单位斜坡响应及稳态误差的计算(Unit impulse response unit impulse response unit ramp response the calculation of the steady-state error)