sat_VSI_12_Pulse

matlab基础教程，从最简单的程序安装开始，适合新手学习(matlab basic tutorials, from the most simple program installation begins, for beginners to learn)

matlab中的主成分分析法，有效的计算了以后预测问题，精度高。(matlab in the principal component analysis, effective after the prediction calculated with high precision.)

递推最小二乘算法递推最小二乘算法递推最小二乘算法递推最小二乘算法递推最小二乘算法递推最小二乘算法递推最小二乘算法递推最小二乘算法(RLS)

3维FDTD pec边界 已调试好( 3-D FDTD code with PEC boundaries)

Name: gmac = global minimization of the active contour model ％ Description: see paper "Fast Global Minimization of the Active Contour/Snake Model" in JMIV07 ％ Author: Xavier Bresson (xbresson@math.ucla.edu) ％ Lastest version: 07-09-21(Name: gmac = global minimization of the active contour model Description: see paper Fast Global Minimization of the Active Contour/Snake Model in JMIV07 Author: Xavier Bresson (xbresson@math.ucla.edu) Lastest version: 07-- 09-21)

在matlab环境下，结合c语言，给出了常用三种图像处理的代码：灰度图像边缘检测，K-L变换，图像的统计直方图。(In the matlab environment, the combination of c language, given the commonly used three types of image processing code: gray-scale image edge detection, KL transform, the image histogram statistics.)

PURPOSE: MCMC estimates Bayesian heteroscedastic AR(k) model imposing stability restrictions using Gibbs sampling y = b0 + y(t-1) b1 + y(t-2) b2 +,...,y(t-k) bk + E, E = N(0,sige*V), sige = gamma(nu,d0), b = N(c,T), V = diag(v1,v2,...vn), r/vi = ID chi(r)/r, r = Gamma(m,k)( PURPOSE: MCMC estimates Bayesian heteroscedastic AR(k) model imposing stability restrictions using Gibbs sampling y = b0+ y(t-1) b1+ y(t-2) b2+,...,y(t-k) bk+ E, E = N(0,sige*V), sige = gamma(nu,d0), b = N(c,T), V = diag(v1,v2,...vn), r/vi = ID chi(r)/r, r = Gamma(m,k))

说明：  基于单尺度、多尺度、原始的Retinex算法，matlab实现，非常值得研究！在光照增强中有着非常好的应用！(Based on single-scale, multi-scale, the original Retinex algorithm, matlab implementation is worth studying! Increase in light has a very good application!)

洛伦兹吸引子的函数程序以及动态图形，matlab程序(Lorenz attractor function procedures and dynamic graphics, matlab program)

matlab中画图功能的详细介绍，给出了几个简单的例题，可直观的看出各种画图的区别(Drawing function in detail, and a few simple examples are given, which can find the intuitive difference of various kinds of drawing)