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📄 tvarma_gen_non.m

📁 用于模拟时变非平稳的ARMA过程
💻 M
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function y= tvarma_gen_non(e, Anm, Bnm)% function y= tvarma_gen_non(e, Anm, Bnm)%   This file is part of the TFPM toolbox v1.0 (c)%   michael.jachan@tuwien.ac.at and underlies the GPL.% % Generates the output of a noncyclic shifted TVARMA(MAR, MMA, 1/2)% model. Zero initial states. The TV model parameters a_m[n]% resp. b_m[n] are given in the N x (MAR+1) resp. N x (MMA+1)% matrices Anm resp.  Bnm, where N is the length of the input% signal vector e. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%if(0)% TEST TEST TEST TEST TEST TEST TEST TEST TEST TEST%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%clear;tfpm;MAR  =   0;LAR  =   0;MMA  =   2;LMA  =   1;N    =  64;re_im= 'r';mo_no= 'm';tfpm_file_gen;%-------------e= randn(N, 1);%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%end;% TEST TEST TEST TEST TEST TEST TEST TEST TEST TEST%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%e= e(:);N= length(e);MMA= size(Bnm, 2)-1;MAR= size(Anm, 2)-1;%% The TVMA part:E= e;for m= 1:MMA   E= [E [zeros(m, 1); e(1:N-m)]];end;u= sum(E.*Bnm, 2);%% The TVAR part:if(~MAR)   y= u;else   amn= Anm;   anm(:, 1)= -u;   yy= [1 zeros(1, MAR)];   y= [];   for n=0:N-1      y= [y; sum(-anm(n+1, :).*yy)];      yy= [1 y(n+1) yy(2:MAR)];   end;end;%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%if(0)% TEST TEST TEST TEST TEST TEST TEST TEST TEST TEST%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%e= randn(N, 1);ynon= tvarma_gen_non(e, Anm, Bnm);ycyc= tvarma_gen    (e, Anm, Bnm);plot(ynon-ycyc)%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%end;% TEST TEST TEST TEST TEST TEST TEST TEST TEST TEST%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

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