community.py

模仿windows里面自带的扫雷游戏而设计的扫雷游戏，完全由VC++设计。-imitation windows inside the mine, bringing their game designed demining game entirely by VC design.

俄罗斯方块源程序 玩过俄罗斯方块的，都知道-Russian box source played the Russian box, we would have known

通过一些基础的程序，讲述C和c++的一些基础知识。(Through some basic procedures on the C and c++ some basic knowledge.)

PRM路径规划源代码，matlab直接运行(PRM path planning source code, matlab run directly)

说明：  lms滤波，可以用于去噪。在标准sin的信号基础上加入高频噪声，均匀白噪声和高斯白噪声，再采用lms滤波，可以得到预期波形(LMS filtering can be used for denoising. The expected waveform can be obtained by adding high frequency noise, uniform white noise and Gaussian white noise on the basis of standard sin signal and using LMS filter.)

我写了个和MS的扫雷长象和玩法都一样,但我的有以下特别功能： 1 开始游戏第一下永远不会点到雷 2 (保存/恢复 )可以在任何时候保存游戏状态，可在任何时候恢复 3 100% 纯 JAVA 编写， 可以在任何系统上运行，比如苹果电脑和LINUX等 4 100% 公开源代码 这个游戏基于MVC架构编写. 把jar文件默认打开程序设为JAVA虚拟机，就可双击JMinesweeper来启动游戏，如果没有装JAVA虚拟机可以去SUN的主页上下载: http://jdl.sun.com/webapps/download/AutoDL?BundleId=9992 把JMinesweeper.jar用WinRAR或WinZip解压后，可以在解压文件夹中找到这个游戏的所有源码。-I wrote a MS-like mine, and games are played are the same, but I have the following functions : starting a game will never be the first to mine two points (preservation/restoration) can be preserved at any time, the game may be resumed at any time 3100% Pure Java prepared, any system running, such as Linux and Apple Computer as 4,100% of the open-source MVC framework based on the game prepared. put jar document procedures set by default to open Java Virtual Machine, JMinesweeper can double-click to start the game, if not installed Java Virtual Machine can go to the home page of the Sun Download : http://jdl.sun.com/webapps/download/AutoDL BundleId = 9992 J

说明：  向滑动幻灯片是一款带箭头按钮跟数字标签的jquery滑块幻灯片(A sliding slide is a jQuery slider slide with arrow buttons and digital labels.)

说明：  用hanning窗的插值FFT算法，适用于电力系统信号的谐波分析(Hanning window with interpolation FFT algorithm, applied to power system harmonic analysis signals)

用H无穷控制，对不稳定系统进行鲁棒控制。本人用车载DVD作了仿真试验，效果较好-H infinite control of instability robust control system. I made a car DVD simulation test, the result is better

the code for a classification neural network