AR2_P33

Matlab+常用图像函数,包括图像的读写,显示,模拟噪声生成函数等(Matlab+ common image functions, including reading and writing images, display, analog functions, such as noise generated)

录制一段自己的语音信号，并对录制的信号进行采样；画出采样后语音信号的时域波形和频谱图；通过matlab界面进行编程设计，界面方便人们操作( Their record a voice signal, and recording the signal is sampled draw sample after the time-domain waveform and frequency spectrum of the speech signal designed by matlab programming interface, easy for people to interface)

基于模型预测控制的驾驶员模型的轨迹跟踪（CarSim8.02和Matlab联合仿真文件）(Tracking (CarSim8.02 and Matlab co-simulation file) trajectory model predictive control based on driver model)

有关雷达的使用的Matlab小程序，相当于雷达工具箱，特别是做雷达控制方面的很有用！(This project is very useful to the people who like doing the radar especially doing the radar control.)

模式识别中的K均值算法，对数据进行归类。程序中，使用了二维数据进行分类。通过修改参数，也可以支持三维或是更高维数的分类。(the K-means algorithm for Pattern Recognition )

matlab上机实验：时域采样与频域采样(Time domain sampling and frequency domain sampling )

逆合成孔径雷达成像，目标直线运动，估计速度后补偿成像，效果很好(Inverse synthetic aperture radar imaging, target linear motion, after an estimated rate of compensation for imaging with good results)

利用matlab软件对.wav音频文件进行降采样的m文件(Down sampling .wav audio file )

K最邻近密度估计技术是一种分类方法，不是聚类方法。 不是最优方法，实践中比较流行。 通俗但不一定易懂的规则是： 1.计算待分类数据和不同类中每一个数据的距离（欧氏或马氏）。 2.选出最小的前K数据个距离，这里用到选择排序法。 3.对比这前K个距离，找出K个数据中包含最多的是那个类的数据，即为待分类数据所在的类。(K nearest neighbor density estimation is a classification method, not a clustering method. It is not the best method, but it is popular in practice. Popular but not necessarily understandable rule is: 1. calculate the distance between the data to be classified and the data in each other (Euclidean or Markov). 2. select the minimum distance from the previous K data, where the choice sorting method is used. 3. compare the previous K distances to find out which K data contains the most data of that class, that is, the class to which the data to be classified is located.)

gmsk的matlab实现，可直接运行，自己编写的，请高手指点！(GMSK matlab to achieve the direct running, I have written, please expert advice!)