仿真程序

基于AFSA的光纤陀螺随机信号建模，跟大家交流下(AFSA based FOG random signal modeling, sharing with you the next)

直接转矩控制算法的实现及其相关设置配置 (DTC control method)

图像处理，用于在MATLAB中播放AVI视频文件。附送标准AVI文件一枚。(Image processing, used to play AVI video files in MATLAB. With a standard AVI file.)

简单六杆机构的matlab编程实例，可求出六杆中各杆的角位移，角速度，角加速度和e点的速度与加速度，并绘制图像。(Simple six institutions Matlab programming examples, can be obtained the rod angular displacement, angular velocity, angular acceleration, and e point in six velocity and acceleration, and draw the image.)

电子工业出版社出版的国外电子与通信教材系列一书：现代通信系统（MATLAB版）（第二版）中的脚本文件与M文件(第二章－－九章) (Electronics Industry Publishing House of foreign electronic communications materials and a series of books : Modern communication system (MATLAB) (2nd edition), the script file and M (Chapter II-- 1109))

遗传算法的matlab工具箱，需要用到遗传算法的同志们可以下载哈(matlab toolbox based on matlab，you can get it to have a look)

混沌工具箱ver.2.0,程序没问题，可以用。有c-c法求时延和嵌入维数的，求最大李雅普诺夫指数的等。(Chaos Toolbox ver.2.0, the program is no problem, you can use. There cc method for delay and embedding dimension, for the largest Lyapunov exponent and so on.)

地震SV波的源代码，得出反射系数，透射系数，转换波的反射系数，透射系数等(SV wave seismic source code, come the reflection coefficient, transmission coefficient, reflection coefficient, transmission coefficient converted waves, etc.)

说明：  （1）应用9×9的窗口对上述图象进行随机抽样，共抽样200块子图象； （2）将所有子图象按列相接变成一个81维的行向量； （3）对所有200个行向量进行KL变换，求出其对应的协方差矩阵的特征向量和特征值，按降序排列特征值以及所对应的特征向量； （4）选择前40个最大特征值所对应的特征向量作为主元，将原图象块向这40个特征向量上投影，所获得的投影系数就是这个子块的特征向量。 （5）求出所有子块的特征向量。 ((1) the application of 9 × 9 window of these images at random, a total sample of 200 sub-image (2) all sub-images according to out-phase into a 81-dimensional row vector (3) all 200 lines for KL transform vector, derived its corresponding covariance matrix of eigenvectors and eigenvalues, in descending order by eigenvalue and the corresponding eigenvector (4) a choice to 40 corresponding to the largest eigenvalue eigenvector as the PCA, the original image block to the 40 feature vectors on the projection, the projection coefficients obtained by this sub-block eigenvector. (5) calculated for all sub-block eigenvector.)

naive bayesian classification