Array-Signal-Processing-program

说明：  本代码是GAUSS-SEIDEL迭代法、选主元JORDAN消去法、简单GAUSS消去法、选主元GAUSS消去法的MATLAB程序，有详细注释，可直接调用(This code is GAUSS-SEIDEL iteration, pivoting JORDAN elimination, simple GAUSS elimination, pivoting GAUSS elimination of the MATLAB program, with detailed notes, can be called directly)

libsvm library for machine learning

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)

求解最短路问题，求解图论中任意两点间最短距离(Solving the Shortest Path Problem)

learn it very useful

MathLab introduction in Romanian.

数据统计与分析【matlab例程】经典算法直接应用方便快捷(Statistics and data analysis routines convenient [] classical algorithm matlab direct application)

这是一个用liblinear进行分类的例子，需要有liblinear环境(Using liblinear to do classification task)

qr法求特征值和特征向量 QR法能够避免矩阵奇异带来的错误，并能求解特征值有重根的情况(qr France seek eigenvalues and eigenvectors QR method can avoid the matrix singularity caused by errors, and can solve the eigenvalue of the double roots)

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