esprit1

说明：  利用MATLAB编写的该代码,可以将数据写入到TXT文件中,里面还赋有说明(Prepared by the use of MATLAB code, the data can be written to TXT file, which is also endowed with that)

a=load( q.txt ) width=input( 请输入窗宽 ) step=input( 请输入步长 ) m=length(a) for i=1:floor((m-width)/step+1) s(i,1:width)=a(1,1+(i-1)*step:width+(i-1)*step) end b=max(max(s)) M=s./b Rs=input( 请输入本体集半径 ) nd=input( 请输入检测器数模 ) k=1 while k<=nd d{k}=rand(1,width) for i=1:floor((m-width)/step+1) if (norm(d{k}-s(i,:)))^2<Rs break end end k=k+1 end for j=1:nd for i=1:floor((m-width)/step+1) R(i)=(norm(d{j}-s(i,:)))^2(a = load (' q.txt' ) width = input (' Please enter the window width' ) step = input (' Enter step size' ) m = length (a) for i = 1: floor ((m-width)/step+1) s (i, 1: width) = a (1,1+ (i-1)* step: width+ (i-1)* step) end b = max (max (s)) M = s./b Rs = input (' Please enter the body set radius' ) nd = input (' Please enter the number of detector modules' ) k = 1 while k < = nd d {k} = rand (1, width) for i = 1: floor ((m-width)/step+1) if (norm (d {k}-s (i ,:)))^ 2 <Rs break end end k=k+1 end for j=1:nd for i=1:floor((m-width)/step+1) R(i)=(norm(d{j}-s(i,:)))^2)

说明：  利用Matlab对2020年的澳大利亚山火进行模拟仿真，可以更直观地体现澳大利亚山火蔓延的过程。(Using MATLAB to simulate the Australian wildfire in 2020 can reflect the process of Australian wildfire spread more intuitively.)

Block Compressed Sensing of Images Using Directional Transforms

智能微粒群为最小二乘支持向量机调参的示例程序（LSSVM+PSO）(Intelligent Particle Swarm and least squares support vector machine modeling(LSSVM+ PSO))

wsn fundemental in matlab

选择适合并和最大比合并的性能比较分析。有详细的代码供参考(Choose to suit and the comparative analysis and maximum ratio combining performance.Has a detailed code for your reference)

simulink ODE first order example

该文档包含了利用深度学习神经网络对分类问题的详细结构(Implement deep networks for digit classification)

simulation of Dynamic Voltage Restorer in MATLAB simulink software.