GUIDEvideo2

LBG code for VQ watermarking

基于matlabd的关于双馈感应风电系统的建模仿真，可以可视化了解系统的动态过程(giving a kind of Modeling and simulation of Doubly Fed Induction generator (DFIG) coupled with wind turbine visualising the advantages of the DFIG over other generators it is being used for most of the wind applications About the different type)

caalcul fourier series in matlab

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.)

XOR using Neural network

Canny Edge Detection

detection of english alphabet

本程序适用于论文Robust Sparse Coding for Face Recognition(this code is for Robust Sparse Coding for Face Recognition)

有关稀疏离散分数阶傅里叶的程序，其中有稀疏脉冲压缩的事例(Procedures for sparse discrete fractional Fourier, which has sparse pulse compression stories)

捷联惯导系统放置在室内测试台上做静态测试，测试时间4500s。 1）取前180数据做粗对准（解析对准法）； 2）取第181s~900s数据做精对准（Kalman滤波法）； 3）从第901s开始做纯惯导解算； 4）用国军标的导航系统位置精度评价方法评估系统定位精度（分别计算CEP50 和 CEP95 下的定位精度）。(The strapdown inertial navigation system was placed on the indoor test bench for static test with a test time of 4500s. 1) take the first 180 data for rough alignment (analytical alignment method); 2) accurate alignment of 181s-900s data (Kalman filtering method); 3) pure inertial navigation solution is performed from 901s; 4) the positioning accuracy of the navigation system is evaluated by the method of position accuracy evaluation of the national military standard (the positioning accuracy under CEP50 and CEP95 are calculated respectively).)