phased-array-radar

5.0 3 ratings Rate this file 30 Downloads (last 30 days) File Size 11.92 KB File ID #30563

分类算法，参数分别为G（相似度矩阵），r（邻居门限），lambda（类门限），返回值A，一个cell数组，每个元素是一个向量，包含了一个类的所有元素。(Classification algorithm parameters are G (similarity matrix), r (neighbor threshold), lambda (class threshold), the return value A, a cell array, each element is a vector containing all the elements of a class.)

matlab code for image to pixels conversion and vice verse

用Matlab直接计算两个矩阵之间的笛卡尔距离，通用性高(Direct calculation using Matlab Cartesian distance between two matrices, general-purpose high)

Exit Chart with advance plot in matlab

Finding the Peaks in ECG and PPG using the turning point algorithm

M.Jankiram chapter 2 on MIMO

用MATLAB实现将灰度图转换为彩色图（伪彩色）(Gray into color image by the use of MATLABP（seudo-color）)

least squre identification method

1998年, Watts和Strogatz 提出了小世界网络这一概念,并建立了WS模型。 实证结果表明,大多数的真实网络都具有小世界特性(较小的最短路径) 和聚类特性(较大的聚类系数) 。 WS小世界模型构造算法 1、从规则图开始：考虑一个含有N个点的最近邻耦合网络，它们围成一个环，其中每个节点都与它左右相邻的各K/2节点相连，K是偶数。 2、随机化重连：以概率p随机地从新连接网络中的每个边，即将边的一个端点保持不变，而另一个端点取为网络中随机选择的一个节点。其中规定，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。 (In 1998, Watts and Strogatz proposed the concept of the small world network, and the establishment of the WS model. The empirical results show that most real networks have small world (the smaller the shortest path) and clustering properties (high clustering coefficient). WS small-world model construction algorithm 1, from the rules FIG: consider a nearest neighbor coupling network with N points, they are surrounded by a ring, wherein each node and its left and right adjacent to each of K/2 connected to the node, K is an even number. The 2 randomized reconnection: randomly with probability p from the new connection on each side of the network, coming section of one of the endpoints remain unchanged, while the other endpoint is taken as the random selection of a node in the network. Which states that between any two different nodes can have at most one edge, and each node can not be connected to its own side.)