项目Dll引用整理工具

电机矢量磁链控制完整28335工程，PWM口，及V/F算法,参数辨识程序,磁场定向程序，从转速测量、参数辨识方面改善性能,转速PI调节,电流闭环 使用PI函数,串口SCI控制，ADC、DQ、CLARKE、park变换；(Debug PWM port, and V/F algorithm, parameter identification program, magnetic field orientation program, improve performance from speed measurement and parameter identification, speed PI adjustment, current closed loop using PI function, serial SCI control, ADC, DQ, CLARKE, park transform ;)

各类终端设备的入网,协调的属性，网关各类宏的相关定义及作用

实现应用VC++读取mat文件，实现VC++与matlab混合编程(Achieve application VC++ to read mat file, to achieve mixed VC++ and matlab programming)

针对散乱点数据，构建出三角网，并追踪出等值线，随后进行填充算法实现。附件中包含有实现源代码工程（VS2008）、编程调试文档笔记、试验数据等。(For scattered point data, construct a triangle mesh, and track the contour, followed by filling algorithm. Implementation annex contains the source code project (VS2008), programming and debugging, documentation notes, test data.)

Viterbi Decoder in C

基于C++编写的，关于狼吃羊的小游戏的一个简单编程。(Based on C++, a simple programming about the game of wolf & sheep.)

利用封装 Winodws Filtering Platform 的WinDivert 库, clumsy 能实时的将系统接收和发出的网络数据包拦截下来，人工的造成延迟，掉包和篡改操作后再进行发送。无论你是要重现网络异常造成的程序错误，还是评估你的应用程序在不良网络状况下的表现，clumsy 都能让你在不需要额外添加代码的情况下，在系统层次帮你达到想要的效果(Using Winodws Filtering Platform package WinDivert library, clumsy can real-time system receives and sends the network data packets intercepted, delay caused by artificial, substitution and tampering after sending operation. Whether you want to reproduce the program errors caused by network exceptions or evaluate the performance of your applications under bad network conditions, clumsy can help you achieve the desired results at the system level without additional code.)

wcdma协议中的turbo码链路仿真,基于bpsk,可以测试误比特率和误帧率等性能(The turbo code link simulation in wcdma protocol, based on bpsk, can test the performance of bit error rate and frame error rate.)

在VS2005环境下开发的几个系统,数据库是用SQL2005(VS2005 environment in the development of some systems, the database is SQL2005)

建立一个bp神经网络解决异或问题：神经网络的结构采用2:2:1的结构，可以改变隐层神经元的个数。(Create a bp neural network to solve XOR problem: the structure of the neural network structure using 2:2:1, you can change the number of hidden layer neurons.)