ar_methods.m

使用MATLAB建立一个AR模型,并画出图形进行比较

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%清理内存
clear
clc
clf
close all hidden 
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% 读入数据方法2：多列数据文件 
the_numline=24;
fni=input('输入数据文件名：','s');
% fni='r0108h2_new.txt';
fni='v15.txt';
begin=1;        %%%开始行
numline=the_numline;    %%%总行数
Nocolume=1;      %%%所选列
Result=FLRead(fni,begin,numline,Nocolume);
x=Result;
%%%  中数法 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% 
   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%% 中数法：滤去低频的确定性信号，并获得零均值有色噪声
   ok_data=true;
   k=1;
   while ok_data
      k=k+1;
      y(k-1)=(x(k-1)+2*x(k)+x(k+1))/4;     % median data
      x0(k-1)=x(k)-y(k-1);                 % cilored noise
      if k==length(x)-1
         ok_data=false
      end
   end    
   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%% 原始数据：绘制原始数据 x-t图
   x=x(2:length(y)+1);
   figure(1)
   k=1:length(x)-2;
   subplot(3,1,1);
   plot(k,x(k));                 %原始数据：绘制原始数据 x-t图
   subplot(3,1,2);
   k=1:length(x)-2;
   plot(k,x(k),'r',k,y(k),'--') % 原始数据：原始数据与确定性成分比较图
   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%% 有色噪声：绘制有色噪声 x-t图
   subplot(3,1,3);
   k=1:length(x)-2;
   plot(k,x0(k));
    
   x=x0;                       % 用于系统分析的有色噪声数据 !!
%%%%%%%%%%%%%%%%%%%%%%%% AR 参数识别
  %%%%%%%%%%%%%% Estimate AR model parameters using Yule-Walker method
p=3;
[a,e,k] = aryule(x,p)
%   %%%%%%%%%%%%%% Estimate AR model parameters using covariance method 
[a,e] = arcov(x,p)
%   %%%%%%%%%%%%%% Estimate AR model parameters using modified covariance method 
[a,e] = armcov(x,p)
%   %%%%%%%%%%%%%%% Linear prediction filter coefficients
% [a,g] = lpc(x,p)