static data member in use

用VB实现文件压缩和解压缩，对于初学VB的同志具有参考价值-VB document compression and decompression, for beginners VB comrades reference value

1.源码太简单 2.不是源码 3.缺少文件 4.所选类别和开发环境不对 5.乱写说明或说明不够认真 6.压缩文件有密码 7.源码重复或已经存在 请不要上传有版权争议的

Compressive Sensing The Big Picture 可以连接到Rice大学等很多网页-Compressive Sensing The Big Picture

图像压缩算法的VC源码，包括了jpeg的压缩编码全过程，很有学习价值。-VC source, including the jpeg compression coding entire process is learning value.

介绍嵌入式的视频,来自上海交通大学,是一个ARM培训的视频教程-introduced Embedded Video from Shanghai Jiaotong University, is a video training ARM Guide

随即算法小课设，ｃ＋＋的写得，大二时写的，有不足之处，敬请谅解-immediately algorithm based small classes, c++ write, write when sophomore, is inadequate, locations

比较不错的压缩算法-quite good compression algorithm

用stl 实现的哈夫曼编码，要是没学过stl 的就不要看了。-with stl achieve Huffman coding, if stl learned not to read it.

conpressive sensing 的MMA新程序- This is an example using the Subspace Pursuit Algorithm of Wei Dai and Olgica Milenkovic "Subspace Pursuit for Compressive Sensing: Closing the Gap Between Performance and Complexity" and the Re-weighted algorithm of Rick Chartrand and Wotao Yin "Iteratively Reweighted Algorithms for Compressive Sensing" In order to run this example you need to install all these m.files in the same directory and type trialSP2 at the prompt. Written by Igor Carron http://nuit-blanche.blogspot.com Creative Commons Licence with attribution

In each step the LZSS algorithm sends either a character or a pair. Among these, perhaps character "e" appears more frequently than "x", and a pair of length 3 might be commoner than one of length 18, say. Thus, if we encode the more frequent in fewer bits and the less frequent in more bits, the total length of the encoded text will be diminished. This consideration suggests that we use Huffman or arithmetic coding, preferably of adaptive kind, along with LZSS.-In each step the LZSS algorithm sends either a character or a lt;position, lengthgt; pair. Among these, perhaps character "e" appears more frequently than "x", and a lt;position, lengthgt; pair of length 3 might be commoner than one of length 18, say. Thus, if we encode the more frequent in fewer bits and the less frequent in more bits, the total length of the encoded text will be diminished. This consideration suggests that we use Huffman or arithmetic coding, preferably of adap