simulate.m

用于模拟时变非平稳的ARMA过程

function [PAR, FLO, STA, AVG, MSE, VAR, BIQ, EInfo]= simulate(exp, N, SNR, par, E, re_im, MM, MAR, LAR, MMA, LMA)
%function [PAR, FLO, STA, AVG, MSE, VAR, BIQ, EInfo]= simulate(exp, N, SNR, par, E, re_im, MM, MAR, LAR, MMA, LMA)
%   This file is part of the TFPM toolbox v1.0 (c)
%   [e-mail] and underlies the GPL.
% 
% This is a meta-function to perform MSE estimates for various
% signal lenghts N, <SNR> values in dB, of re_im-valued parameter
% estimators. 
%
% The matrix <par> is the reference value for the parameters <PAR>
% to be estimated, <E> is the expected energy of the generated
% signal used to compute the noise variance. <MM> is the ensemble
% size. The various parallel running estimators are defined in the
% script tfpm_simu_define_<exp>.m. Data generation of the noisy data
% vector is done in the script tfpm_simu_generate_<exp>.m. The
% TF-multiwindow is defined in tfpm_simu_win_<exp>.m. The
% estimation of unwindowed second-order signal statistics is done
% in tfpm_simu_stat_<exp>.m. Before/after each estimation the
% defpre/defpos script is called. STA is the status of the
% estimator. 

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
if(0)% TEST TEST TEST TEST TEST TEST TEST TEST TEST TEST
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
clear;tfpm;
N    =  64;
MAR  =   2;
LAR  =   2;
MMA  =   1;
LMA  = LAR;
re_im= 'r';
mo_no= 'm';
N0= N;
N= 128;
tfpm_file_gen;
%-------------
N= N0;
alpha= 1/2;
beta = 1/2;

%exp= 'tfma';par= param_expand(Bml, N);E= tfarma_ambi(Aml, Bml, N, alpha);E= E(N/2+1, N/2+1);
%exp= 'tfar';par= [Aml(:, 2:end) Bml];E= tfarma_ambi(Aml, Bml, N, alpha);E= E(N/2+1, N/2+1);
exp= 'tfarma';par= [Aml(:, 2:end); param_expand(Bml, N)];E= tfarma_ambi(Aml, Bml, N, alpha);E= E(N/2+1, N/2+1);

% SNR values in dB
%SNR= [10 6 3 0 -3 -6 -10];
SNR= inf;

% Ensemble size
MM= 10;
mm= 1;snr= 1;ee= 1;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
end;% TEST TEST TEST TEST TEST TEST TEST TEST TEST TEST
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

% Number of parameters:
NPAR= size(par, 1)*size(par, 2);
alpha= 1/2;
beta = 1/2;

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% DEFINE THE ESTIMATORS AND THEIR CALLS
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
defpre_string= sprintf('tfpm_simu_defpre_%s', lower(exp));
define_string= sprintf('tfpm_simu_define_%s', lower(exp));
defpos_string= sprintf('tfpm_simu_defpos_%s', lower(exp));
eval(defpre_string);
eval(define_string);
eval(defpos_string);
esti= size(ESTI, 1);

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% DEFINE THE DATA GENERATION
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
generate_string= sprintf('tfpm_simu_generate_%s', lower(exp));

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% DEFINE THE WINDOW FUNCTION
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
win_string= sprintf('tfpm_simu_win_%s', lower(exp));
eval(win_string);

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% DEFINE THE ESTIMATION
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
stat_string= sprintf('tfpm_simu_stat_%s', lower(exp));

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% ESTIMATE
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

% Parameter array:
PAR= zeros([size(par), MM, length(SNR), esti]);

% Flops counter:
FLO= [];

% Status flag:
STA= [];

for mm= 1:MM
   for snr= 1:length(SNR)
      variance= E/N/10^(SNR(snr)/10);
      eval(generate_string)
      sprintf('%s, N= %4d, SNR= %3ddB, mm= %4d%d%d%d%d', exp, N, ...
	      SNR(snr), mm, MAR, LAR, MMA, LMA)
      eval(stat_string);
      flopsee= [];
      statee = [];
      for ee= 1:esti
%	 ee
%	 sprintf('1')
            eval(SPRE(ee, :));
%	 sprintf('2')
	 flops(0)
%	 sprintf('3')
            eval(ESTI(ee, :));
%	 sprintf('4')
	 flopsee= [flopsee flops];
%	 sprintf('5')
            eval(SPOS(ee, :));
%	 sprintf('6')
	 statee = [statee estistat];
%	 sprintf('7')
         PAR(:, :, mm, snr, ee)= estimate;
%	 sprintf('8')
      end;
      FLO= [FLO; flopsee];
      STA= [STA; statee];
   end;
end;

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% STATISTICAL RESULTS
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
AVG= zeros([size(par), length(SNR), esti]);
VAR= AVG;
BIQ= VAR;
for snr= 1:length(SNR)
   for ee= 1:esti
      AVG(:, :, snr, ee)= mean(PAR(:, :, :, snr, ee), 3);
      VAR(:, :, snr, ee)= abs(std(PAR(:, :, :, snr, ee), 1, 3)).^2;
      BIQ(:, :, snr, ee)= abs(   (AVG(:, :, snr, ee)-par)).^2;
      [M, V, B]= param_mse(PAR(:, :, :, snr, ee), par);
   end;
end;
MSE= BIQ+VAR;