The-car-obstacle--avoidance

利用matlab读取TXT文档并显示，统计文档中某个字符出现的概率并显示，输入替换字符对文档中的某个字符进行替换。(Matlab TXT file to read and display the probability of occurrence of a certain character in the statistical document and display, enter the replacement characters to replace one of the characters in the document.)

matlab的以部分源码，不错啊，对编程很有用的(matlab to use part of the source, yes ah, right programming very useful)

这是一个用MATLAB做的指纹图像，希望对大家有用(This is a use MATLAB to do the fingerprint image, in the hope that useful)

系统聚类法的matlab程序，根据指定类间距离来对数据进行分类(System clustering method matlab program, according to the distance between the specified class data classification)

graphcuts算法，MATLAB编写，可以运行，能直观看到结果。(graph cuts algorithm，MATLAB prepared)

收集的matlab符号运算的电子书籍与文档资料，对于熟悉了matlab数值运算想对符号计算有所了解的可以看看。(Matlab symbolic operation collected the e-books and documentation, for those familiar with the matlab numerical computation would like to understand the symbolic computation can take a look at.)

this is the code for factorial, fft, fftsine

svm的回归预测分析，包含源代码和数据，测试可用(svm regression analysis to predict, including source code and data, test available)

HERE I HAD ATTACHED THE CODES FOR COMPRESSION

DTW算法的程序，申请两个n*m的矩阵D、d,分别为累积距离和帧匹配距离。这里n和m为测试模版与参考模版的帧数。然后通过一个循环计算两个模版的帧匹配距离d。接下来进行动态规划，为每个格点 （i，j）都计算其三个可能的前续格点的累积距离D1，D2，D3。考虑到边界问题，有些前续格点可能不存在，因此加入一些判断条件最后利用最小值函数min()，找到三个前续格点的累积 距离作为累积距离，与当前帧的匹配距离d（i，j）相加，作为当前格点的累积距离。该计算过程一直达到格点（n，m），并将D（n，m）输出，作为模版匹配的结果。(DTW algorithm procedures, apply two n* m matrix D, d, respectively, accumulated distance and frame matching distance. Where n and m is a reference test pattern and the template frames. Then through a loop to calculate two frames template matching distance d. Next, dynamic programming, for each grid point (i, j) are calculated from the cumulative D1 before the renewal of its three possible lattice point, D2, D3. Taking into account the boundary problem, some former continued grid point may not exist, so add some conditions to determine the final use of the minimum function min (), found three former continued accumulation of grid points cumulative distance as the distance from the current frame to match the d (i, j) added, and a current cumulative distance grid. This calculation has reached the grid (n, m), and D (n, m) output, as a result of template matching.)