matlab-art

MULTIAGENTS 4 AGENTS, FORMATION PROBLEM

遗传 算法 ，基于matlab实现，通过选择、交叉、变异，经过多次的迭代从而找到最优个体(Genetic algorithm, based on matlab implementation, through selection, crossover, mutation, after several iterations to find the best individual)

用matlab编写的2维FDTD算法程序，与大家共享(using Matlab prepared by the two-dimensional FDTD algorithm procedures, and share)

pmsg grid connected control

说明：  近年来，基于启发式的多目标优化技术得到了很大的发展，研究表明该技术比经典方法更实用和高效。有代表性的多目标优化算法主要有NSGA、NSGA-II、SPEA、SPEA2、PAES和PESA等。粒子群优化(PSO)算法是一种模拟社会行为的、基于群体智能的进化技术，以其独特的搜索机理、出色的收敛性能、方便的计算机实现，在工程优化领域得到了广泛的应用，多目标PSO(MOPSO)算法应用到了不同的优化领域[9~11]，但存在计算复杂度高、通用性低、收敛性不好等缺点。 多目标粒子群（MOPSO）算法是由CarlosA. Coello Coello等在2004年提出来的(In recent years, heuristic-based multi-objective optimization technology has been greatly developed, and research shows that this technology is more practical and efficient than classical methods. Representative multi-objective optimization algorithms mainly include NSGA, NSGA-II, SPEA, SPEA2, PAES and PESA. Particle Swarm Optimization (PSO) algorithm is an evolutionary technology based on swarm intelligence that simulates social behavior. With its unique search mechanism, excellent convergence performance, and convenient computer implementation, it has been widely used in the field of engineering optimization. The objective PSO (MOPSO) algorithm is applied to different optimization fields [9~11], but it has shortcomings such as high computational complexity, low versatility, and poor convergence. The multi-objective particle swarm optimization (MOPSO) algorithm was proposed by Carlos A. Coello Coello et al. in 2004)

matlab图形处理函数 matlab图形处理(matlab graphics processing function matlab graphics)

这是阵列信号MUSIC算法的程序，是最小二乘ＭＵＳＩＣ的，已经测试过了(This is the MUSIC algorithm for array signal process, is the least squares MUSIC, and has tested the)

基于UWT变换的去噪，利用的是硬阈值来设置阈值门限的(UWT transform based denoising, using the hard threshold to set the threshold value threshold)

说明：  标准粒子群优化算法,适用于matlab。方便实用(Standard particle swarm optimization for matlab. Convenient and practical)

实现基于逆傅里叶变换法下，不同级别道路的路面不平度仿真。(Implementation based on inverse Fourier transform, the different levels of road simulation of road roughness.)