MATLAB-MIMO

一个可以直接应用于扩频系统的m序列仿真，m序列具有很好的自相关性，是在扩频系统中应用最广的伪随机码，本程序可以直接在matlab上运行，对于扩频系统的学习有很大帮助。(Can be directly applied to a m-sequence spread spectrum system simulation, m sequences with good autocorrelation in the spread spectrum system, the most widely used pseudo-random code, the program can be run directly in matlab for Spread Spectrum Systems of great help in learning.)

ICA(独立成分分解),可实现采集信号中源信号的分离，便于提取特征量，实现模式识别。同时由于可以将源信号分离开来，可实现信号的降噪，去掉基波、三次谐波、五次谐波等(ICA (independent component decomposition) can realize the separation of the source signals in the acquisition signal, and facilitate the extraction of the feature quantity, and realize the pattern recognition. At the same time, because the source signal can be separated, it can realize the noise reduction of signal, remove the fundamental wave, the three harmonic, the five harmonic, etc.)

说明：  用小波函数sym6对散斑图像进行4-5层得阈值滤波，并提取相位和去包裹(denoising using wavelet)

matlab工具箱，神经网络 很全面，超星版(matlab toolbox, neural network is very comprehensive, Superstar Edition)

matlab 的文件读取写入代码集合,可以直接调用。(The matlab file read write code set, can be called directly.)

信号与系统中的音乐合成实验，用matlab合成的曲子。(Signals and Systems in music synthesis experiments using matlab synthesized music.)

混合动力汽车永磁同步电机的研究，构建了整车系统，并且研究的分数阶控制器在系统中的控制作用，与整数阶控制器进行了比较(Hybrid permanent magnet synchronous motor research, build the system of the vehicle, and the research of fractional order controllers in the system control function, and an integer order controllers are compared )

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.)

说明：  《MATLAB小波分析》书本实例源程序。 希望为各位的学习带来方便！(MATLAB wavelet analysis examples of source books.I want to bring convenience to learning!)

典型混沌信号的序列生成，以及相空间作图。可以根据自己的需要修改参数(henon signal sequence generation, as well as the phase space mapping. You can modify the parameters according to their needs)