SIMULINKforbeginners

混沌时间序列多步自适应预测方法，非常有用，采用自适应算法，比局部算法要准确(chaos time series prediction)

bouncing ball in matlab

不同算法对时间序列进行奇异谱分解的源程序代码，matlab2006a平台调试通过(different algorithms on time series singular spectral decomposition of the source code, matlab2006a through debugging platform)

通过按钮的回调函数将txt文档中的数据读到listbox1中的函数(The data read txt document listbox1 function button callback function)

基于统计的方差比率计算程序。用于财务金融的建模与分析(Variance ratio based on statistics calculation program. For Modeling and Analysis of Financial)

this file contains a good matlab code for data classification

这是求导波中lamb波频散方程很好的MATLAB代码 绝对好用(To solve the dispersion curve of lamb wave by use of MATLAB program)

基于matlab平台中蚁群算法在三维路径规划研究(Research on 3D path planning based on Ant Colony Algorithm in Matlab platform)

说明：  一个bp网络拟合非线性模型的例子，参考了李国勇书中的公式(A bp network nonlinear model fitting example, with reference to the book' s formula Li Guoyong)

说明：  粒子群算法（PSO）是一种基于群体的随机优化技术。与其它基于群体的进化算法相比，它们均初始化为一组随机解，通过迭代搜寻最优解。不同的是：进化计算遵循适者生存原则，而PSO模拟社会。将每个可能产生的解表述为群中的一个微粒，每个微粒都具有自己的位置向量和速度向量，以及一个由目标函数决定的适应度。所有微粒在搜索空间中以一定速度飞行，通过追随当前搜索到的最优值来寻找全局最优值。 PSO模拟社会采用了以下三条简单规则对粒子个体进行操作：①飞离最近的个体，以避免碰撞。②飞向目标。③飞向群体的中心。这是粒子群算法的基本概念之一。 粒子群算法其基本思想是受许多鸟类的群体行为进行建模与仿真研究结果的启发(Particle swarm optimization (PSO) is a population based stochastic optimization techniques. Based on evolutionary algorithms compared with other groups, they are initialized to a random solution, iterative search through optimal solution. The difference is: the principle of survival of the fittest evolutionary computation to follow, while PSO simulation community. The potential of each solution expressed as a group of particles, each particle has its own position vector and the velocity vector, and a fitness determined by the objective function. All particles in the search space at a constant speed flight, by following the current search to find the optimal values ​ ​ of the global optimum. PSO simulation community has adopted the following three simple rules for the operation of individual particles: ① recently departed individuals, in order to avoid collisions. ② to the target. ③ fly to center groups. This is one of the basic concepts of particle swarm algorithm. PSO algori)