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说明：  nlms和lms算法的matlab仿真程序（1）(nlms matlab and lms algorithm simulation program (1))

Python Matlab Converter, version 2.2 Runs in Python

多目标多学科优化，目标解析分流法ATC的简单例子(Multi Objective, Multi Disciplinary, Analytical Target Cascading (ATC) Demo)

matlab ı ı r code for pic application

1. 判断闰年 根据输入的具体年份（在1900-2100之间，要求对输入进行有效性检查），判断是否闰年，并给出相应的提示信息 (1. To determine leap year according to input a specific year (in 1900-2100 between the call for input validation), to determine whether a leap year, and gives the corresponding tips)

一堆沙子的横截面，可以使用 Margolus 型邻居仿真，但运动规则不同。 规则： 元胞有 2 个状态。状态= 0 是空的，状态= 1 代表沙子。 在任何时间步长，一个粒子，可以在2x2 块中向着底部运动。可能运动如下 所示。墙壁和底部将阻止粒子继续运动。 为了让该运动略有随机性，我亦补充说一项规则，有时处于下落状态的两个元胞还旋转，直到所有的动作都完成。(Cross-section of a pile of sand, you can type using the Margolus neighborhood simulation, but the movement rules are different. Rules: There are two cellular states. State = 0 is empty, state = 1 for sand. At any time step, a particle can be in the 2x2 block toward the bottom of the movement. May exercise the following. Walls and bottom to prevent the particles continue to campaign. To make the campaign a little random, I also added a rule, sometimes in the falling state of the two cell also rotate until all actions are completed.)

此源码会产生一个平方空间上随机的领域。样品创建拉丁超立方抽样和空间相关性是基于Cholesky分解算法(This source will generate a random field on a square space. Samples to create a Latin Hypercube Sampling and spatial correlation is based on the Cholesky decomposition algorithm)

一种无线通信网中的用户移动模型，用来描述仿真中小区内分布的用户及其移动规律。(User moves in a wireless communication network model, used to describe the simulation of small and medium-sized district distribution of users and their movement law.)

带电圆环的电势分布图，利用matlab求解带电圆环的电势分布图(Charged electric potential distribution ring)

NW小世界网络的构成原则为：从一个环状的规则网络开始，网络含有N个结点，每个结点向与它最近邻的K个结点连出K条边，并满足N>>K>>In(N)>>1。随后进行随机化加边，以概率p在随机选取的一对节点之间加上一条边。其中，任意两个不同的节点之间至多只能有一条边，并且每一个节点都不能有边与自身相连。改变p值可以实现从最近邻耦合网络(p=0)向全局耦合网络(p=1)转变。在p足够小和N足够大时，NW小世界模型本质上等同于WS小世界模型。 (NW constitutive principles of small-world networks: from the rules of a ring network, network with N nodes, each node is connected to the K node with its nearest neighbor K edges, and meet N > > K > > In (N) > > 1. Followed by randomization into the plus side, with probability p with an edge between a pair of nodes in a randomly selected. Wherein between any two different nodes at most only one edge, and each node can not have a side connected with itself. P value can be changed to achieve the transition from the nearest neighbor coupling network (p = 0) coupled to the global network (p = 1). When p is small enough and large enough N, NW small-world model is essentially the same as the WS small-world model.)