matlab from entry to senior advanced essential books, looking after, in the hope...

本课件是本人多年来教学实践中积累和制作的《操作系统》这门课程的教学课件（ppt格式），使用多次学生反映较好，有较高实用价值。-Courseware is the teaching practice over the years I accumulated and the production of the "system" of this curriculum courseware ( ppt format), use better reflect the number of students, which have a higher value.

DirectShow开发指南9,PDG格式,请自己解压-DirectShow Development Guide 9, PDG format, extract themselves

该MFC参考含盖了Microsoft基本类库中的类、全局函数、全局变量和宏的内容。 -The MFC reference covers the Microsoft Foundation Class in the class, global function, global variables and macro elements.

全面揭示PE文件的核心机密!彻底揭开PE结构的面纱!-comprehensive document reveals the core secrets! PE completely open structure of the veil!

Navida之GPU编程资料。3d图形开发必备资料！-Navida of GPU programming information. 3d graphic development of essential information!

OPENCV下的入门介绍以及配套源码，简单易学，中科院自动化所的一个牛人写的！-Started under OPENCV introduction as well as ancillary source, easy to learn, the Chinese Academy of Sciences Institute of Automation, a cow who write!

ASP基础教材. -ASP foundation teaching material

iptables是linux下功能强大的防火墙管,有NAT支持，但网上的手册不多，分享一下下！-iptables is a powerful firewall under linux pipe, there are NAT support, but the online manual not much to share next!

这是网页制作必看的一份资料，个人觉得很有用，收获很大，喜欢网页制作的朋友不妨下载看看吧-This is the web of an information watched every game, feel useful and very fruitful. like web friends may wish to download and watch it

小波变换在信号处理、图像处理、模式识别、计算机视觉等 方面广泛应用。本文提出了一种基于Haar小波的时问序列相似 模式匹配模型．它首先对时间序列数据进行Haar小波变换．以 降低数据的维度。首先将所要查询的时间序列进行降维，也就是 对时间序列数据进行小波变换，对序列进行标准化131，得到降维 之后的小波序列．这样可以得到系数子集的良好近似采用尺度 序列表示原始序列．并将其看成多维空间中的一个点，通过计算 两序列差的平方和的平方根作为这两个时间序列的距离函效 (即欧氏距离)。用小波变换保持了局部性质。而欧氏距离就是要 判断相似性的距离函数．所以当在作完变换之后。通过低频分量 来压缩数据，成功的计算出实际距离的下界。如果计算的结果小 于一个由用户所定义的门槛值．则认为这两个时问序列是相似 的。 在-Of wavelet transform in signal processing, image processing, pattern recognition, computer vision, etc. Aspects of wider application. In this paper, Haar wavelet-based time series similarity Pattern matching model. It is first time-series data, Haar wavelet transform. To To reduce the data dimension. Will first want to check the time series dimension reduction, that is, Pairs of time series data using wavelet transform, standardize the sequence 131, to be reduced- After the wavelet sequence. This can be a good approximation coefficients of a subset of the use of scale Seque