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LMS和RLS自适应算法性能比较(The comparation of LMS and RLS in adapinve signal processing)

ACF中包含两个m文件，一个是自协方差函数（可单独使用）。另一个是自相关函数计算，其调用autocov函数。(ACF contains two m files, one is self-covariance function (which can be used alone). The other is calculated from the correlation function, which calls autocov function.)

说明：  实现任意直线对多边形的分割，返回生成的多边形顶点坐标(An arbitrary line of division of the polygon，Return vertex coordinates of polygons generated )

根据邻接矩阵作图 matlab实现 源代码(mapping according to the adjacency matrix )

说明：  matlab求解TSP问题源代码，程序可动态显示路径寻优过程(matlab source code for solving TSP problems, the program can show the path of dynamic process optimization)

利用最小距离分类器分类３种鸢尾属植物 load fisheriris 载入Matlab自带的鸢尾属植物数据集 每类的前40个样本用于生成代表该类的模板，后10个作为独立的测试样本(Plant data sets The first 40 of each class used to generate the samples representative of the class template 10 after the test sample as separate)

something about physics

Matlab源程序：MMSE Receiver for DS-SS in AWGN Channel！希望对大家有帮助。(Matlab source : MMSE Receiver for DS-SS in AWGN Channel! We want to help.)

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)

此源码构建的模型是基于MATLAB平台，采用bragg结构，高效率发光管的光学结构设计。分别给出p波和s波的分量。(Construction of this source model is based on the MATLAB platform, using bragg structure, high efficiency LED optical structure design. Were given p-wave and s-wave component.)