Fimp-T-correction

Smith预估控制算法和PI控制算法的联合运用(Smith)

基于李雅普诺夫稳定性模型参考自适应控制的参考程序(based on Lyapunov stability theory of model reference adaptive control)

二维相位解包裹；用相移法和傅里叶变换法重建物光场相位(Two phase solution package)

一个实现vc与matlab接口的程序，可在vc构建的平台上实现matlab的函数调用(a realization vc Matlab interface with the procedures in vc build on the platform to achieve the function call Matlab)

Matlab code various programs. Matlab code various programs. Matlab code various programs.

matlab开发的模糊pid控制器,用simulink平台实现,有一定的典型性(Matlab pid development of the fuzzy controller, using Simulink platform. have some typical)

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)

pml boundary of 2-d Tmz wave

matlab语音端点检测源码,对非连续性语音具有良好的检测性能(vad in process of speech)

This matlab code is intended to demonstrate the physical significance/interpretation of the elements of diagonal matrix in Singular Value Decomposition (SVD). Here, multiple rows of a BIG matrix is gradually being filled with ones which means the information content is being reduced. Now, the eigenvalues and their 1st and 2nd derivatives are plotted.