C# examples network. There are many practical examples of C#

面向.net的全新工具 《C#完全手册》-Oriented. Net new tools

液晶驱动芯片HT16512的使用,以及应用的程序-LCD Driver IC HT16512 the use and application procedures

Calculator program written by DLLs with the math algorithms such as automata and can draw some simple graphs.

MFC 高级编程。该书是英文版的，共有16章，书中有大量的源代码，对大家学习提高很有帮助-MFC programming. The book is the English version of a total of 16 chapters, the book has a lot of source code, we learn to improve helpful

深入浅出Linux设备驱动编程,从基础介绍Linux设备驱动开发-In layman" s language and Linux device driver programming, from basic introduction to develop Linux device drivers

FILE VIEW : made by prf.mr SONG in korea. This file describe rendering skill for study smoke(SPH).

C语言实现的表达式求值程序，由用户输入一个中缀表达式，系统自动求值，表达式中只含有加减乘除和括号这5种运算符。-C language implementation of the expression evaluation process from the user to enter an infix expression, the system automatically evaluated, the expression contains only addition and subtraction multiplication and division, and parentheses which five kinds of operators.

是我下载的测试mfc用ado技术连接数据库的示例-I downloaded a test mfc technology using ado to connect the sample database

bmp位图文件的读取与保存 bmp位图文件的读取与保存，可以借此熟悉bmp的文件结构-bmp bitmap file to read and save bmp bitmap file to read and save, you can take with bmp file structure

本文完成了对唇动身份识别技术几个基本问题的理论研究,并对整个系统加以实现.作为本文研究的实验基础,我们建立了唇动方式身份识别数据库(HITLUDB), 该库目前包含30个说话人每人20个汉语词的音视频语料.数据库的扩充与完善工作仍在不断的进行之中.在嘴唇检测方面, 我们对自适应色度过滤模型进行改进,提高了算法的鲁棒性,完成了对嘴唇的精确定位.结合DCT变换与K-L变换的各自特点, 我们提出了特征提取算法,使用较少维数的特征完成了对嘴唇区域主要信息的刻画.由于唇动信息同时包含了生理特征与行为特征, 我们使用静念动念混合建模的方式,完成了对说话人唇动个性特点的精确描述.在HMM训练时,我们提出了特征的归一化处理方法,提高了HMM在实际应用中的性能. 最后,我们分别对身份辨认系统与身份确认系统的基本理论进行了叙述,并完成了系统的实践工作. 关　 键　 词：身份识别 唇动 特征提取 隐马尔可夫模型 K-L变换 -paper completed the lip movements identification technology several basic issues of theoretical study, system as a whole be achieved. As this paper, the experimental basis, We have established a dynamic manner lip identification database (HITLUDB) The library currently contains 30 words each of 20 Chinese words, sound and video corpus. and the expansion of the database is still perfect keep going on. Detection of the lips, we adaptive color filter model improvements, improve the robustness of the algorithm, completed a pair of lips the precise positioning. DCT combined with