MATLABfunction

MATLAB编写界面很复杂，通过这个文档你能很快的实现(Written MATLAB interface is complex, through this document you can quickly achieve)

基于VB／MATLAB的前兆资料小波分析程序的实现(Based on the VB/MATLAB wavelet analysis of the precursor process information to achieve)

基于YCbCr颜色空间的人脸分割程序，且对大量实验图片验证均有效(YCbCr color space based on face segmentation procedure, and the picture of a large number of experimental verification are valid)

this matlab code helps the image processing lerners to denoise grey images as well as other applications having denoising applications.

1.IMM.m 主要功能： （1）IMM算法的实现； （2）画出目标轨迹与利用IMM算法跟踪目标的轨迹； （3）画出位置误差与速度误差； （4）画出模型混合概率图。 2.Target_track.m 主要功能： 实现目标轨迹的产生。 3.Model_mix.m 主要功能： 实现IMM算法下，各模型的估计融合。 4.Kalman.m 主要功能： 实现模型的条件滤波，以及似然函数的输出。(1.IMM.m main functions: (1) IMM algorithm implementation (2) Draw the locus and utilization of IMM target tracking algorithm goals (3) shows the position error and speed error Mixed (4) Draw model probability plots. 2.Target_track.m main functions: to produce the target locus. 3.Model_mix.m main functions: IMM algorithm, it is estimated each model integration. 4.Kalman.m main functions: the model filter condition, and it seems natural function of the output.)

我写的一个小程序。用MATLAB自动生成任意维数和任意数量的数据，并且根据这些数据用一定的方法统计出这些点的概率密度。(I wrote a small program. MATLAB automatically generated using an arbitrary dimension and arbitrary amount of data, and based on these data in a certain way to the statistics of the probability density of these points.)

普通PID控制跟踪正弦信号的matlab M文件仿真例子。在这个例子里面可以看到跟踪信号有一定的超前现象。( 英语 中文(简体) 日语 Ordinary PID control matlab M file tracking sinusoidal signal simulation example. In this example can be seen that the tracking signals have a certain advance phenomenon.)

runga kutta numerical integration method

说明：  其中为MPC模型预测控制仿真程序，为m文件，包含了对模型预测控制的理解，有助于结合理论(MPC model predictive control simulation program, m file, contains the understanding of model predictive control, which is helpful to combine theory)

C-C方法计算时间延迟和嵌入维数计算Lyapunov指数计算关联维数混沌时间序列预测(The C-C Method is used to calculate the embeded dimension and Lyapunov exponents.It can be used to forcast the time series.)