QMF2

用mathlab解关于卫星轨迹图的微分方程组, 简单实用的例子,能从中知道如何编写程序, 并如何画图.可直接在matlab7.0中运行. 以及有关于复杂网络的matlab源程序，供致力于复杂网络仿真研究的同仁参考！(Appollo satellite s trace (Differential equation))

介绍了m 序列和Gold 序列的原理、性能和构造方法，接着在MATLAB 中用M 语言编程实现它们的产生和分析。(Describes the m-sequence and Gold sequence of principle, performance and construction methods, and then using M language in MATLAB programming their generation and analysis.)

用于分析线列阵宽带，可以修改参数，自己编写，仅供参考(For the analysis of line array broadband, you can modify the parameters, write your own, for reference only)

基于MATLAB的原理应用，此程序可实现2d的吸收边界算法，比较简单(This MATLAB M-file implements the finite-difference time-domain solution of Maxwell s curl equations over a two-dimensional Cartesian space lattice comprised of uniform square grid cells.)

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.)

使用MATLAB生成棋盘矩阵,希望对大家有帮助(Use MATLAB to generate chessboard matrix, in the hope that everyone has to help)

自己做的： （一）用双线性变换法设计并用实验系统实现一个三阶的契比雪夫Ⅰ型低通数字滤波器，其采样频率Fs =8KHz，1DB通带边界频率为fp=2KHz。 （二）用双线性变换法设计并用实验系统实现一个三阶的契比雪夫Ⅱ型高通数字滤波器，其采样频率Fs =16KHz，阻带边界频率为fst =4KHz，As=20dB。 ((A) design using the bilinear transformation method and the experimental system of a third-order Chebyshev low-pass type Ⅰ digital filter, the sampling frequency Fs = 8KHz, 1DB passband boundary frequency is fp = 2KHz. (B) Bilinear transformation method used to design and use of the experimental system of a third-order Chebyshev type Ⅱ high-pass digital filter, the sampling frequency Fs = 16KHz, stopband boundary frequency fst = 4KHz, As = 20dB.)

包含试验得到的风速普，Kaimal谱及其曲线，可以在ANSYS里加载。(This source contains several wind speed spectrum,such as Kaimal spectrum.)

说明：  分别应用jacobi迭代和gseid迭代进行方程的求解，并且比较两种迭代方法的精度 和效率(Were applied jacobi iteration to iteration and gseid equation, and compare the two precision and efficiency of iterative methods)

Character Recognition Example (I&II)- Pre-processing of Image (Matlab Code)(Character Recognition (I)