zuixiaoerchengfa

在matlab环境中模拟单管燃油加热的管壁及油温的变化，分为在高温下考虑裂解和不考虑裂解俩种情况(In the matlab environment simulation single pipe fuel heating tube wall and the change of the oil temperature, divided into under high temperature to consider cracking and not consider cracking two kinds of cases)

A three-body simulation matlab small procedures, parameters can be modified after the track and watch planetary motion picture production

Wang mendel fuzzy model paper

绘制二维非线性系统的相图，MATLAB程序，自已编写，多多交流！(Phase diagram, drawing two-dimensional nonlinear system MATLAB program, written, more exchanges!)

源代码在matlab实现相邻帧间差分法对于视频中对移动目标的识别。附送视频，在matlab上能打开的视频只有无压缩的AVI视频。视频背景没有变化的情况下，处理效果很好。(The source code in matlab between adjacent frame difference method for the recognition of moving target in the video. Attached to the video, can open the video on the matlab only compressed AVI video. Does not change the background of video cases, the treatment effect is very good.)

刚来了本书《MATLAB 7.x数字信号处理》，作者郭仕剑。在此把光盘内容共享出来， 包括数字信号处理常用函数列表和常用的程序集(First came to the book, "MATLAB 7.x digital signal processing" of Guo Shi sword.In this CD-ROM content sharing, including digital signal processing a list of commonly used functions and assembly)

地震勘探数据处理的matlab工具包，包括常用的反褶积，拉登变换，地震绘图等多种功能，比较好用的小东西(Seismic data processing matlab toolkit, including the commonly used deconvolution, transform Laden, seismic mapping and other features, compared to-use small things)

Genetic algorithm in matlab.

A DC/DC Boost Converter was developed using the simulink tool box

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.)