2011-12-23-1337

用于学习软判决解调算法,文件中包含用于算法描述的文献,以及对应matlab代码,支持PSK,QPSK,16-QAM,64-QAM四种调制方式(Demodulation algorithm for learning soft decision, contained in the file for the algorithm described in the literature, as well as the corresponding matlab code support PSK, QPSK, 16-QAM, 64-QAM four modulation)

矩形遍历检测窗口演示Matlab源代码,用于理解Haar-like的功能(Haar-like rectangular detection window traversal demo Matlab source code for understanding Haar-like functions)

Matlab decision tree code

少数者获胜博弈，用matlab仿真模拟实验(minority game，with matlab simulation)

自适应滤波器的lms算法，包括误差，频谱等性能仿真(Lms adaptive filter algorithms, including error, such as performance simulation of spectrum)

采用栅格对机器人的工作空间进行划分，再利用优化算法对机器人路径优化，是采用智能算法求最优路径的一个经典问题。目前，采用蚁群算法在栅格地图上进行路径优化取得比较好的效果，而利用遗传算法在栅格地图上进行路径优化在算法显得更加难以实现。 利用遗传算法处理栅格地图的机器人路径规划的难点主要包括：1保证路径不间断，2保证路径不穿过障碍。 用遗传算法解决优化问题时的步骤是固定的，就是种群初始化，选择，交叉，变异，适应度计算这样，那么下面我就说一下遗传算法求栅格地图中机器人路径规划在每个步骤的问题、难点以及解决办法。(It is a classical problem to divide the workspace of the robot by grids and optimize the path of the robot by using optimization algorithm. At present, the ant colony algorithm is used to optimize the path on the grid map, and the genetic algorithm is used to optimize the path on the grid map, which is more difficult to achieve. The difficulties of using genetic algorithm to deal with the path planning of robot on raster map mainly include: 1. guaranteeing that the path is uninterrupted, 2. guaranteeing that the path does not cross obstacles. The steps of genetic algorithm in solving optimization problems are fixed, that is, population initialization, selection, crossover, mutation, fitness calculation. Then I will talk about the problems, difficulties and solutions of genetic algorithm in each step of robot path planning in raster map.)

基于matlab，利用信息熵法排序。例子为对学校进行排序(Based on matlab, using information entropy ordering. Examples of the sort of school)

Mean Shift Clustering

Audio Watermark coding

m现代通信系统－使用matlab,该书的所有程序(m modern communication systems- using matlab, the book all the procedures)