theuseofmatlabinthetimeseries

人脸识别算法基本代码matlab源代码1(face recognition)

Face Recognition Based on Statistical Moments

使用matlab求解一元函数最大值问题的代码(Solving functions of one variable maximum )

已知: 每个飞机只有一个油箱， 飞机之间可以相互加油(注意是相互，没有加油机) 一箱油可供一架飞机绕地球飞半圈，问题:为使至少一架飞机绕地球一圈回到起飞时的飞机场，至少需要出动几架飞机?(所有飞机从同一机场起飞，而且必须安全 返回机场，不允许中途降落，中间没有飞机场)(plane problem)

DOA baemforming for one monopole

Adaptive clustering algorithm

random number generator

说明：  粒子群优化算法(Particle Swarm optimization,PSO)又翻译为粒子群算法、微粒群算法、或微粒群优化算法。是通过模拟鸟群觅食行为而发展起来的一种基于群体协作的随机搜索算法。通常认为它是群集智能 (Swarm intelligence, SI) 的一种。它可以被纳入多主体优化系统(Multiagent Optimization System, MAOS)。粒子群优化算法是由Eberhart博士和kennedy博士发明。(The probabilistic neural network has a simple structure and is easy to design Particle Swarm Optimization (PSO) is translated as Particle Swarm Optimization, Particle Swarm Optimization, or Particle Swarm Optimization. It is a random search algorithm based on group collaboration developed by simulating the foraging behavior of birds. It is generally considered to be a type of swarm intelligence (SI). It can be incorporated into Multiagent Optimization System (MAOS). The particle swarm optimization algorithm was invented by Dr. Eberhart and Dr. Kennedy.)

产生一个随机数序列,具有高斯统计特征，可用于载波仿真。(create a random sequence with gaussian statistical features,which can be used in carrier wave stimulation )

根据公汽线路信息数据，编写对任意车站，寻找通过该站的汽车线路的M文件； （3）编写M文件，对任意两个车站m,n，判断是否有线路通过这两车站，若有则编写寻找通过该站的汽车线路的M文件 （4）对任意两个车站m,n，若没有线路直接通过这两车站，编写通过一次转车而到达两站的M文件 (According to the bus line information and data to write on any station to find the M-file line through the station car (3) the preparation of the M-file, any two stations m, n, determine whether the line through these two stations, if write to find the M-file line through the station car (4) any two stations m, n, if there is no line directly through the two stations, the preparation time to change trains to reach the M-file of the two stations)