SMI

说明：  DE算法 经典的算法，来自于英文文献，适于研究DE算法(Simple DE algorithm )

分析声音信号的时域和频域特性，并且可以分析声卡输入的声音，自己产生信号(Analysis of the sound signal in time domain and frequency domain characteristics, and can analyze the sound of the sound card input, the generated signal)

Xport Transport Stream Demuxer Updated 09/06/2007 - current version is 0.98(Xport Transport Stream Demuxer Updated 09/06/2007- current version is 0.98)

This package contains some MatLab tools for multi-scale image processing. Briefly, the tools include: - Recursive multi-scale image decompositions (pyramids), including Laplacian pyramids, QMFs, Wavelets, and steerable pyramids. These operate on 1D or 2D signals of arbitrary dimension. Data structures are compatible with the MatLab wavelet toolbox. - Fast 2D convolution routines, with subsampling and boundary-handling. - Fast point-operations, histograms, histogram-matching. - Fast synthetic image generation: sine gratings, zone plates, fractals, etc. - Display routines for images and pyramids. These include several auto-scaling options, rounding to integer zoom factors to avoid resampling artifacts, and useful labeling (dimensions and gray-range).

一本很好的MATLAB书籍，里面讲述的内容非常基础，适合入门学习(MATLAB a very good book, the content of which is about very basic, suitable for beginners to learn)

GUI摩斯码转换器，实现摩斯码与英文的相互转换并发出声响(GUI Morse code converter)

说明：  rs码基于matlab编码，c语言译码，已验证，为正确代码(rs encoding with matlab,and decoding with c)

这个是基于角点的匹配和拼接的MATLAB算法程序，如果有用得到的，可以参考！(is based on the corner of the match and combinations of MATLAB algorithm procedure, if the useful, reference!)

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.)

该程序是基于数值分析的计算的三次样条插值和最佳平方逼近，用c做的，有注释，代码简单，希望能对您有用(The program is based on the numerical analysis of the calculated cubic spline interpolation and best square approximation, with c do, Notes, code simple, hoping to be useful for you)