MATLAB

说明：  内存dc，内存dc是用于双缓冲，以解决重绘闪烁的问题(Memory dc, memory dc for double buffering to resolve the issue of flickering redraw)

用FORTRON程序编的最速下降法，用来解决无约束规划问题(With FORTRON program compiled the steepest descent method, which is used to solve the unconstrained programming problem)

计算机视觉工具箱,对计算机视觉相当有帮助.(Computer Vision Toolbox for computer vision has considerable help.)

常用分形matlab程序（经测试）具体为几种常见混沌时间序列matlab实现(Commonly used fractal matlab program (tested) specific for several common realization of chaotic time series matlab)

三角剖分matlab实现的三角剖分，形成网格模型(Triangulation matlab achieve triangulation, to form a grid model)

精通matlab7.1让您详细的学习matlab，快速登堂入室(Proficient matlab7.1 you a detailed study matlab, quickly reached a higher level)

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.)

用于求解PM波浪谱，matlab编程，随机波浪课程应用(Used to solve P-M wave spectrum)

GVF SNKE 模型matlab源代码(gvf snake)

多进制LDPC码的高斯消去方法的matlab源代码(Binary LDPC codes Gaussian elimination method matlab source code)