Matlabshixi

this may use ful this for u

说明：  ARIMA 模型是在平稳的时间序列基础上建立起来的，因此时间序列的平稳性是建模的重要前提。检验时间序列模型平稳的方法一般采用 ADF 单位根检验模型去检验。当然如果时间序列不稳定，也可以通过一些操作去使得时间序列稳定（比如取对数，差分），然后进行 ARIMA 模型预测，得到稳定的时间序列的预测结果，然后对预测结果进行之前使序列稳定的操作的逆操作（取指数，差分的逆操作），就可以得到原始数据的预测结果。(time series prediction ARIMA)

用matlab实现高斯—若当算法求逆矩阵(Using matlab to achieve Gauss- Jordan matrix inversion algorithm)

HMMBOX, version 3.2, William Penny, Imperial College, Feb 1999 Matlab toolbox for Hidden Markov Models(HMMBOX, version 3.2, William Penny, Imperial College, Feb 1999 Matlab toolbox for Hidden Markov Model s)

Matlab Sample Codes Implementation

Generating an Optical Sensor Image From Simulated Movement Data This script (aero_pointer_tracker.m) generates a movie with 64 frames and a frame size of 64 by 64 pixels (at 10 frames per second). The movie contains a simulation of a moving target that is moving through a structured background that is itself moving. A jitter motion caused by random vibration is also generated (in a Simulink® model called "aero_vibrati") and the jitter motion is added into the overall sensor motion. Finally, the image is blurred through a Gaussian optical point spread function. Note: Changing delt here also requires a change in the parameters set-up dialog box in the Simulink model "vibration".

颜色空间转换。。。。。。。。。。。。。。。。。。。。。(Color space conversion)

This is code to simulation of AM, FM, PSK, QAM modulation

MATLAB 傅里叶分析 快速傅里叶分析 非常正确的资料 值得下载(MATLAB FFT)

fourier series coefficient