seven-degreesmodel

svd with LDA face recognition feature extraction

计算序列的自相关函数,绘制信号xn的自功率谱幅频曲线,绘制信号yn的自功率谱幅频曲线,计算互谱函数(Calculating the autocorrelation function of the sequence, drawn from the power spectrum of the signal xn amplitude-frequency curve, drawn from the power spectrum of the amplitude-frequency curve signal yn calculated cross-spectral function)

perform cross correlation between two time series

用于仿真正负线性调频信号在同时极化测量中的性能(Simulation of positive and negative for the chirp signal at the same time measuring the performance of polarization)

用matlab实现聚类算法，注意是层次聚类和未知类别聚类算法！(Clustering algorithm using matlab implementation, pay attention to are hierarchical clustering and unknown type of clustering algorithm!)

An object-oriented C++ implementation of Davidson method for finding a few selected extreme eigenpairs of a large, sparse, real, symmetric matrix(An object-oriented C++ Implementation of Davidson method for finding a few selected extreme eigenpairs of a large, sparse, real, symmetric matrix)

这个程序可以模拟脉冲体制雷达的动、静目标回波，并进行距离压缩，MTI，MTD(This program can simulate pulse radar system dynamic and static target echo, and range compression, MTI, MTD)

改进节点法建立MNA方程 matlab算法，附有设计文档(Modified nodal equations matlab algorithm established by MNA)

任务： 1） 借助MATLAB画出误差性能曲面和误差性能曲面的等值曲线（参考PPT2.1第17页的两幅图）； 2） 写出最陡下降法以及LMS算法的计算公式（取 ）； 3） 用MATLAB产生方差为0.05, 均值为0白噪音S(n)，并画出某次采样得到的波形（即产生任意一个噪声随机序列）； 4） 根据 2）中的公式，并利用 3）中产生的S(n)，在 1）中的误差性能曲面的等值曲线上叠加画出采用最陡下降法以及LMS法时H(n)的在叠代过程中的轨迹曲线（参考PPT2.1第17页的右下图的曲线1和曲线2）。 5）用MATLAB计算并画出LMS法时 随时间n的变化曲线（对应S(n)的某一次的一次实现）和e(n)波形； 注意：某一次实现的结果并不能从统计的角度反映实验的结果 的正确性，为得到具有统计特性的实验结果，可用足够多次的 实验结果的平均值作为实验的结果。用MATLAB计算并画出 采用LMS法时，J(n)的100次实验结果的平均值随时间n的变 化曲线（即 生成随机噪声信号并计算结果，重复执行100次， 求平均结果）。 6）在 1）中的误差性能曲面的等值曲线上，叠加画出采用LMS法得到的100次实验中的H(n)的平均值的轨迹曲线； (Task: 1 ) Draw with MATLAB error performance surface and surface contour error performance curve ( refer PPT2.1 two chart on page 17 ) 2 ) Write the steepest descent method and the LMS algorithm formula ( take ) 3 ) Using MATLAB to generate variance of 0.05 with a mean of 0 white noise S (n), and draw a particular sampling waveform ( ie, any noise generated random sequence ) 4 ) based on 2 ) of the formula , and use 3 ) generated in S (n), in a ) the error performance curves superimposed on the surface contour plot using the steepest descent method and the LMS method when H (n) the iterative process in the trajectory curve ( refer PPT2.1 page 17 bottom right of the curves 1 and 2 ) . 5 ) using MATLAB LMS method is used calculate and draw the curve with time n (corresponding to S (n) of a first implementation of a ) and e (n) waveform Note : in a first implementation of the results are not reflected from a statistical point of view of accuracy of the experimental results ,)

二维小波分析在图像平滑、融合与增强中的应用(D wavelet analysis in image smoothing, integration and enhancement of)