mel1

The sparsity of signals and images in a certain trans-form domain or dictionary has been exploited in many applications in signal and image processing. Analytical sparsifying transforms such as Wavelets and DCT have been widely used in compression standards. Recently, synthesis sparsifying dictionaries that are di-rectly adapted to the data have become popular especially in appli-cations such as image denoising, inpainting, and medical image re-construction.

analysis numeric, polinom 4 deg

实现发动机性能的计算，在matlab环境下简单可靠的运行(this can use at matlab to engine)

lmd 采用滑动平均处理，调整过，可以直接运行出图。(lmd hua dong pingjun)

MATLAB 入门的教程，适合新手学习使用(this is for matlab new learners)

Nprot application for tumor segment

data hiding in audio signal, using matlab

book which helps on developing matlab files for motors

GM(1,1) Predictor (Grey Model)

分类算法，参数分别为G（相似度矩阵），r（邻居门限），lambda（类门限），返回值A，一个cell数组，每个元素是一个向量，包含了一个类的所有元素。(Classification algorithm parameters are G (similarity matrix), r (neighbor threshold), lambda (class threshold), the return value A, a cell array, each element is a vector containing all the elements of a class.)