chan

稀疏贝叶斯学习是一种很好压缩感知，信号恢复方法。(sparse bayesian learning is a good cs method for coefficient recovery.)

用来测试压缩感知中构造的测量矩阵的RIP的(this .m file is used to check the senging matrix RIP in CS)

说明：  matlab 用PCA方法对图像进行压缩、还原(PCA method using matlab image compression, restore)

说明：  这是一个常用的JPEG-LS编解码的C语言实现。(This is a commonly used JPEG-LS codec C language.)

说明：  一篇关于压缩感知的经典文章，压缩感知（Compressed sensing，简称CS，也称为Compressive sampling)理论异于近代奈奎斯特采样定理，它指出：利用随机观测矩阵可以把一个稀疏或可压缩的高维信号投影到低维空间上，然后再利用这些少量的投影通过解一个优化问题就可以以高概率重构原始稀疏信号，并且证明了这样的随机投影包含了原始稀疏信号的足够信息。(A classic article on compressed sensing, compressive sensing (Compressed sensing, referred to as CS, also known as Compressive sampling) different from the modern theory of the Nyquist sampling theorem, which states: the use of a random measurement matrix can be sparse or compressible high-dimensional signal projected to low dimensional space, and then use a small amount of projection by solving an optimization problem to be sparse with high probability to reconstruct the original signal, and prove that random projection of the original sparse signal contains enough information.)

说明：  c语言环境下的 RLE编码的串行程序(c language environment RLE encoded serial procedures)

顺序表插入删除，典型的教科书式的程序。老师给的。。。。。。(The order of the table insert removed, a typical textbook-style programs.)

基于wavelet和bandelet的spiht图像压缩！(And wavelet-based image compression spiht the bandelet!)

solver PMD (optical fiber)

ansys 分析 圆环的受力:一个的圆环,受一对过直径的集中 应力, 作用下发生1mm的压缩量（如图所示）。已知材料的弹性模量E＝2.0GPa，泊松比为0.3。用平面应力单元PLANE82分析圆环内部的应力分布情况(ansys analysis by the Circle : A Circle and the one across the diameter of the concentrated stress, occurred under 1 mm compression volume (as shown). Known material elastic modulus E = 2.0GPa, Poisson's ratio of 0.3. Plane stress analysis modules PLANE82 Circle internal distribution of the stress)