m_sequence-genetate-AND-nature-test

该matlab代码实现了“综合多分支分裂式层次化聚类” (Matlab implementation of Omnibus Multi-Branching Divisive Hierarchical Clustering (OMBDHC) “A competitive omnibus performance criterion for divisive multi-branching hierarchical clustering” by Soeria-Atmadja et al. (submitted). Note that OMB-DHC package is implemented in Matlab code and therefore demands the Matlab core program, as well as the Statistics toolbox of Matlab. Divisive hierarchical clustering (DHC) has emerged as a promising alternative for the identification of sub-structures in multivariate data. Of particular interest is multi-branching DHC, which allows flexible numbers of subclusters at each hierarchical level. One poorly explored issue in multi-branching DHC concerns the actual importance of the two performance criteria (and their associated algorithms) to automatically create clusters and select number of clusters, respectively. Another interesting but hitherto unexplored issue is the possibility to employ a single omnibus performance criterion that guide)

qr decompostion using new method

matlab中VCA算法的事例 用于高光谱像元解混(the algorithm of VCA)

phase space reconstruction for both univarite and multivarite time series

calculating secant Value

傅里叶变换和小波变换重建图像的比较效果，这个程序可以用来实现四个要求：1、FFT和WT重建效果比较；2、通过改变小波来比较重建效果；3、通过改变分解层数来比较重建效果；4、通过改变大系数个数来比较重建效果。其中还有一个计算PSNR的程序(the comparative effect of reconstruction image by Fourier transform and wavelet transform 。 the program can be used to achieve the four requirements: 1, FFT, and WT reconstruction effect 2, by changing the wavelet to compare the reconstruction effect 3, by changing the decomposition layers to compare the reconstruction effect 4, by changing the number of large coefficient of comparative reconstruction results. Including a procedure of calculating PSNR )

说明：  随机共振是一种新颖的信号降噪方法，适量的噪声能够共振出隐含的特征频率。(SR is a good method to denoise signals.)

matlab code for generation of data to svpwm

matlab 图像/视频处理实例整本书第一到第十章源码(matlab used in processing in images)

对二维图像进行ROI提取的程序，提供GUI界面(A GUI to find ROI in 2D image)