reflected-waves-model

说明：  matlab最常用命令 1.有关命令行环境的一些操作:  (1) clc 擦去一页命令窗口,光标回屏幕左上角  (2) clear 从工作空间清除所有变量  (3) clf 清除图形窗口内容  (4) who 列出当前工作空间中的变量  (5) whos 列出当前工作空间中的变量及信息  或用工具栏上的 Workspace 浏览器 (matlab command most commonly used 1. on the command-line environment, a number of operations:  (1) clc remove a command window, the cursor back to the top left corner of the screen  (2) clear working space from the removal of all variables  (3) clf clear the graphics window content  (4) who are listed in the current working space of variable  (5) whos lists the current working space of variables and information  or Workspace toolbar browser)

说明：  OBS汇聚算法，用matlab实现，该算法为混合门限汇聚算法(OBS aggregation algorithm, using Matlab realize that the algorithm for mixed Threshold aggregation algorithm)

矩阵相乘，基于CUDA用并行算法实现矩阵的乘法(matrix muliplication with parallel algorithm implication matrix muliplication base on CUDA )

This code consists of the frost filter coding.

关于医学图像处理的matlab实现的代码和报告，包括几种常用的matlab分割方法(Medical Image Processing on the realization of the matlab code and reports, including several commonly used segmentation matlab)

DMI 矩阵逆分解 随期望信号的增大的算法估计的变化(DMI matrix inverse decomposition increases with the expected signal changes in the algorithm estimates)

主要讲述了matlab相关的数学问题的解答，很全面。(Focuses on matlab related mathematical questions, very comprehensive.)

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.)

Written for engineering and computer science students and practicing engineers, this book provides the fundamental applications and mathematical techniques of signal processing. Topics covered include programming in MATLAB, filters, networking, and parallel processing. MATLAB is introduced and used to solve numerous examples in the book. Companion software available In addition, a set of MATLAB M-files is available on a CD bound in the book.

matlab时频分析工具箱，分析信号时频特性。(Matlab time-frequency analysis toolbox, analysis of the time-frequency characteristics of the signal.)