svctools

粒子群算法的程序，主要是针对基本粒子群和改进粒子群算法。(Particle swarm optimization procedures, mainly for the basic particle swarm optimization and improved particle swarm algorithm.)

说明：  针对一般的粒子群优化(PSO)学习算法中存在的容易陷入局部最优和搜索精度不高的缺点,对改进型PSO算法进行研究。由于惯性权重系数ω对算法是否会陷入局部最优起到关键的作用,因此,通过改变惯性权重ω的选择,对惯性权重系数采取线性减小的方法,引入改进型的PSO算法。采用改进的PSO算法对PID控制器进行参数优化并把得到的最优参数应用于控制系统中进行仿真。仿真实验结果表明:改进型PSO算法不会陷入局部最优,能得到全局最优的PID控制器的参数,并使得控制系统的性能指标达到最优,控制系统具有较好的鲁棒性。(Aiming at the shortcomings of general PSO learning algorithm, which is easy to fall into local optimum and low search precision, the improved PSO algorithm is studied)

mSequence_generatorM序列发生器.rar是基于MATLAB编器的M序列发生器(mSequence_generatorM sequence generator. rar is based on MATLAB)

标准粒子群优化算法Matlab 源代码 放心可用(PSO ALGORITHM matlab)

以NACA0012 翼型为研究对象，采用拉格朗日法分析了重力对水滴撞击特性的影响，获得了过冷大水滴(SLD)撞击特性。(The influence of gravity on the droplet impingement property were analyzed with the Lagrangian method, and the supercooled large droplet (SLD) impingement property has been gotten based on the research of NACA0012 airfoil)

经测试可以运行的MATLAB编程实现混合蛙跳算法(After the test you can run MATLAB programming realize SFLA)

matlab实现的基于模糊逻辑的一个简单小例子，仿真已通过，可供初学者实践。(matlab fuzzy logic-based implementation of a simple small example, simulation has been adopted practice for beginners.)

说明：  一个随机数产生器(mt19937) 计算物理中Monte Carlo方法中的基本条件 周期为2^19937(a random number generator (mt19937) Computational Physics Monte Carlo methods of the basic conditions for the cycle 2 ^ 19937)

基于笛卡尔网格的自适应网格生成，实现方式相对简单，灵活易用。(PARAMESH is a package of Fortran 90 subroutines designed to provide an application developer with an easy route to extend an existing serial code which uses a logically cartesian structured mesh into a parallel code with adaptive mesh refinement(AMR).)

李纯明最新实现的局部活动轮廓模型的图像分割，比CV模型方法好很多。包含所实现的论文Minimization of Region-Scalable Fitting Energy for Image Segmentation(Li Chunming latest realization of the local active contour model for image segmentation, much better than the CV model approach. The paper contains the realization of Minimization of Region-Scalable Fitting Energy for Image Segmentation)