LFSR

segmenting image processing using lazy snaping

M/M/1 模型,主要用来求解单对单服务台的模型，过程比较简介，适合任何分布(M/M/1 model, mainly used to solve the one-on-one help desk model, the process is relatively brief, suitable for any distribution)

此代码应用于将xml文件转换为mat文件。在图像的目标识别时我们需要获得一些图像的点坐标。但是通过label me。我们只能获得xml文件的形式，这样我们就需要将xml文件转换为mat文件。方便在matlab的语言环境中进行处理(This code is used in the xml file into mat file. When the target image recognition we need at some point in image coordinates. But by label me. We can only get in the form of xml files, so we need to convert the file to mat xml file. Facilitate processing matlab language environment)

可实现光流、惯性、地磁组合导航的扩展卡尔曼滤波算法(This program can realize the integration if optical flow/INS/magnetic.)

一个变压器励磁涌流的仿真案例，考虑磁滞的影响(A transformer inrush current simulation case, consider the impact of hysteresis)

模式分类工具箱，SVC,PCA等,核分类，带例子以及所需数据(PatternClassificationToolBox，PCA,quadrat,kernels,bayes)

matlab例程，非常好用，便以移植,bianyuxuxi(susan Algorithm is very easy to use, then to transplant)

program to find the classification using matlab programming

说明：  TFBSS是一种基于短时傅里叶时频分析的盲源分离算法，算法基于卷积混合。处理非平稳源信号。(TFBSS performs Blind Source Separation of (over)determined multiplicative mixtures of non-stationary real valued sources. TFBSS is based on the joint-diagonalization of whitened and noise-compensated Spatial Time-Frequency Distribution (STFD) matrices of the observations, corresponding to single auto-terms positions, as described in: C. Févotte and C. Doncarli. "Two contributions to blind source separation using time-frequency distributions", IEEE Signal Processing Letters, 2004. IEEE Signal Processing Letters, vol. 11, no. 3, Mar. 2004. pdf and A. Holobar, C. Févotte, C. Doncarli, and D. Zazula. "Single autoterms selection for blind source separation in time-frequency plane". In Proc. 11th EUSIPCO, Toulouse, France, 2002 (Special Session on Source Separation). pdf )

数字图像频域滤波处理，分别进行二阶巴特沃斯(Butterworth)高通、低通滤波器。(Digital image processing frequency domain filtering, respectively second-order Butterworth (Butterworth) high pass, low pass filter.)