LBP

利用c++实现图像转置源代码，像素变换的一种方式(use Image home to the source code, pixel transform the way)

A control system of the simplex method of PID parameter optimization of MATLAB program, can also

图像傅利叶变换源码程序，结合易语言位图操作支持库，通过傅利叶公式的计算变化图像。(Fourier transform image source program , combined with easy language support library bitmap operations , by calculating the Fourier formula change images.)

本程序实现Bilateral滤波，以实现边缘保留的平滑处理，同时可用于灰度及彩色图像。(Bilateral filtering realize this procedure in order to achieve a smooth edge to retain the handle at the same time can be used for gray and color images.)

压缩感知去噪代码，一种用于去噪的CS的有效代码，简单适用(Compressed sensing denoising code, one for denoising CS valid code, a simple application )

根据RBM深度网络（Hinton，2006）进行MINST手写文字的分类器的训练，利用训练得到的权值制作了这个小程序，通过这个程序可以看出训练结果对数据集内的测试样本和训练样本都能进行很好的识别，但是对其他的手写字体识别就没有那么好了。(According to RBM depth network (Hinton, 2006) conducted MINST handwritten text classifier training, using the training to get the right value to produce this small program, this program can be seen through the results of the training data set and the training sample test samples are can be well identified, but on the other handwriting recognition is not so good.)

粒子滤波去噪程序 目标跟踪 粒子滤波的实验程序( particlefilter target tracking)

this codes describe several kind of image filters

水平集(level set)的基本思想是将界面看成高一维空间中某一函数ψ（称为水平集函数）的零水平集，同时界面的演化也扩充到高一维的空间中。我们将水平集函数按照它所满足的发展方程进行演化或迭代，由于水平集函数不断进行演化，所以对应的零水平集也在不断变化，当水平集演化趋于平稳时，演化停止，得到界面形状。(The level set (level set) the basic idea is to interface as a higher dimensional space in a function (called a level set function) of the zero level set, and the interface evolution also extended to higher dimensional space. We evolve or iterate the level set function according to the evolution equation it satisfies. Because the level set function keeps evolving, so the corresponding zero level set is also changing. When the level set evolves to a stable state, the evolution stops, and the interface shape is obtained.)

本文首先概述了独立成分分析与盲信号分离， 主成分分析的关系， 然后系统地介绍了该技术的基本概念和数据模型， 对现今比较流行的各种独立成分分析算法进行了剖析和总结。最后对独立成分分析的发展及应用前景作了展望(In this paper, an overview of independent component analysis and blind signal separation, principal component analysis of the relationship, and then systematically introduces the basic concept of the technology and data models for today' s more popular variety of independent component analysis algorithm is analyzed and summarized. Finally, independent component analysis of the development and application prospects are described)