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genetic algorithm In the field of artificial intelligence, a genetic algorithm (GA) is a search heuristic that mimics the process of natural selection. This heuristic (also sometimes called a metaheuristic) is routinely used to generate useful solutions to optimization and search problems.[1] Genetic algorithms belong to the larger class of evolutionary algorithms (EA), which generate solutions to optimization problems using techniques inspired by natural evolution, such as inheritance, mutation, selection, and crossover.

模糊自适应PID控制仿真模型，模糊控制的一个例子(PID and Fuzzy control)

Binary data generator

实现全搜索运动估计算法，实现三步法快速搜索算法(achieve full search motion estimation algorithm, the three-step realization of Fast Search Algorithm)

说明：  word里面是粒子群算法的Pareto多目标函数优化的程序(Pareto multi-objective function optimization based on particle swarm optimization)

用matlab计算脉冲在光纤中传输的薛定谔方程。(Calculated using matlab pulse in optical fiber transmission Schrö dinger equation.)

16 Quam modulation and link budget calulation for SATCOM

基于蚁群算法的优化实现路径最短的问题程序(Based on ant colony optimization algorithm to achieve the shortest path problem program)

本程序是基于支持向量机的图像分割问题。通过支持向量机对图片的采样点进行训练，然后对整张图片进行预测。可以将图片分为前景与背景两个部分。(This procedure is based on the support vector machine image segmentation problem. Through the support vector machine to the picture of the sampling point for training, and then the whole picture to predict. Images can be divided into two parts: foreground and background. )

对图像rgb分割，输入图像，可得到R.G.B分别图像。最终得出分割图像(Rgb image segmentation, the input image, each RGB image available. The final segmented image obtained)