Matlab零相位滤波（基于巴特沃斯模拟滤波器）

用Matlab实现的人脸检测算法. Based on the paper: Face Detection using Local SMQT Features and Split Up SNoW Classifier(Face Detection algorithm for Matlab. Based on the paper: Face Detection using Local SMQT Features and Split Up SNoW Classifier)

goldenman binormial tree matlab code

遗传算法（Genetic Algorithm，GA）是通过对自然界中生物的遗传和优胜劣汰的进化过程进行模拟与抽象，进而形成的一种自适应全局随机优化搜索方法。遗传算法只需提供目标函数作为寻优信息，它从某一随机生成的初始群体出发，经过选择、交叉和变异等遗传操作后对个体进行适应度评价，保留适应度较强的个体遗传到子代种群中，经过多次的迭代计算求得最优个体，即问题的最优解。本程序采用遗传算法可求解微网优化运行。(Genetic Algorithm is an adaptive global by nature, genetic and biological survival of the fittest evolutionary process simulation and abstract, and thus the formation of stochastic optimization search method. Just provide genetic algorithm optimization objective function as an information, which is generated from a random initial population of departure, after genetic manipulation, such as selection, crossover and mutation of individuals fitness evaluation, retained a strong individual genetic fitness to child on behalf of the population, after several iterations of computing the optimal solution to get the optimal individual, that is the problem. This program uses a genetic algorithm to solve the optimal operation of the micro-network.)

说明：  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.)

matlab code for Hilbert Huang Transform part (matlab code for Hilbert Huang Transform part)

file pathloss .....................................................

snake模型寻找图像边界，以及改进的GVF算法(snake model for image border, and to improve the algorithm GVF)

for read and write multiple image

很好的MATLAB教程，思路清晰，有助于初学者快速学号MATLAB(Good MATLAB tutorials, clear thinking, helps beginners quickly learn No. MATLAB)

说明：  matlab智能算法数值分析数值优化路径规划人工智能神经网络(Matlab intelligent algorithm 30 examples, learn numerical algorithms and artificial intelligence path planning numerical optimization)