基于元胞自动机的微观交通流建模仿真

一个横好的谱估计算法，AM ma 和arma模型，可以自动的选取。(A good cross-spectral estimation algorithm, AM ma and arma model selection automatically.)

说明：  帮同学弄得一个小程序，交作业用的，各位老大指点(To help students confused)

模拟退火算法的解决 具体在mATlab实现算法 (matlab)

最小生成树算法的matlab实现，自己写的(good for learning)

基于哈小波的图像稀疏分解与重构。并进行MATLAB仿真。图像为经典lena图像(Image sparse decomposition and reconstruction based on wavelet. And the MATLAB simulation. The classic image to Lena image)

小波变换进行变速箱故障诊断 首先将s1和s2信号时域谱（s1代表维修前的振动信号，s2代表维修后的振动信号），画出来进行对比，会发现s1信号的振动幅值会比较高；然后对s1和s2分别进行小波分解并画出各层的时域谱，只对比s1和s2分后的最高时域谱，s2更加的具有周期性，且幅值较小，s2周期性不够明显，且振动过于密集。分析完时域谱后开始分析频谱，首先对原信号s1和s2fft转换，得到频谱图，如图，然后再对小波分析后高频部分进行fft转换，做出频谱图。对比后我们发现，在f 2375HZ出（也就是齿轮的啮合频率），s1信号频谱幅值会有急剧的升高，然后，其谐波的幅值也会增大。所以可以推断出该维修前的增速箱的齿轮可能出现问题。(Gearbox fault diagnosis based on wavelet transform s1 and s2 first time domain signal spectrum (s1 behalf of the vibration signal before maintenance, vibration signal s2 representative of repaired), drawn comparison, you will find a signal s1 vibration amplitude will be higher then s1 and s2 respectively wavelet decomposition and draw the layers of time-domain spectrum to only a maximum time domain spectroscopy s1 and s2 points after, s2 is more cyclical and smaller magnitude, s2 cyclical enough obviously, and the vibration is too dense. End domain spectral analysis after the beginning of the spectrum analysis, the first of the original signal s1 and s2fft conversion to give the spectrum, as shown, and then after the high frequency part of wavelet analysis fft transformation to make spectrum. We found that after the comparison, at f 2375HZ out (i.e. the gear mesh frequency), there will be a sharp increase in the amplitude spectrum of the signal s1, and then, the amplitude of the ha)

动态窗口法，直接可以运行的程序。实乃学习路径规划优良demo( Dynamic window method, you can run the program directly. Learning Path planning exercise good demo)

说明：  Resolution geometrique pour encoder incremental

signals n systems matlab codes

对角加载波束形成算法，包含信噪比以及信干噪比的仿真图(Diagonally loaded beamforming algorithm, including simulation diagrams of signal-to-noise ratio and signal-to-interference-to-noise ratio)