VSS&SM_code_集员滤波_集员_apa_仿射自适应滤波器_

% Adaptive filter using Basic Affine Projection Algorithm and % clear all; close all; clc; L = 5000; %input data size N = 40; %filter length w0 = zeros(N,1); %initialization for adaptive filters mu1 = 0.05; %step-size parameter mu2 = 0.2; mu3 = 1; mu_max = 1; %the maximum value of the step-size parameter SNR_dB = 30; %SNR epsilon = 1e-4; %regularization parameter MCruns = 100; %Monte Carlo simulation runs C1 = 1e-5; C2 = 1e-4; C3 = 1e-6; h = [0.1, -0.2, -0.3, 0.4, 0.4, -0.2, -0.1]; W = [ones(1,20), 0, -ones(1,19)]; mse_apa = zeros(L,1); % MSE vectors for Monte Carlo simulations mse_apa1 = zeros(L,1); mse_apa2 = zeros(L,1); mse_vssapa = zeros(L,1); mse_vssapa1 = zeros(L,1); mse_vssapa2 = zeros(L,1); msd_apa = zeros(1,L); % MSD vectors for Monte Carlo simulations msd_apa1 = zeros(1,L); msd_apa2 = zeros(1,L); msd_vssapa = zeros(1,L); msd_vssapa1 = zeros(1,L); msd_vssapa2 = zeros(1,L); for I = 1:MCruns x = filter(h,1,randn(L,1)); %input data y = filter(W,1,x) ; %desired response ey2=mean(y.^2); sgma=sqrt(ey2*1e-3); %SNR=30dB gama=sqrt(5)*sgma; vk=sgma*randn(1,L); d=y+vk; % I % % Full-update APA % P = 4; %APA order [eAPA,w] = full_apa(x,d,N,P,w0,mu1,epsilon); %mu = 0.05 mse_apa = mse_apa + eAPA.^2; w_opt = W; for ii = 1:L msd_apa(1,ii) = msd_apa(1,ii) + norm(w(ii,:)-w_opt)/norm(w_opt); end [eAPA1,w] = full_apa(x,d,N,P,w0,mu2,epsilon); %mu = 0.2 mse_apa1 = mse_apa1 + eAPA1.^2; for ii = 1:L msd_apa1(1,ii) = msd_apa1(1,ii) + norm(w(ii,:)-w_opt)/norm(w_opt); end [eAPA2,w] = full_apa(x,d,N,P,w0,mu3,epsilon); %mu = 1 mse_apa2 = mse_apa2 + eAPA2.^2; for ii = 1:L msd_apa2(1,ii) = msd_apa2(1,ii) + norm(w(ii,:)-w_opt)/norm(w_opt); end % % VSS-APA % P = 4; %APA order [eVSSAPA,w] = vss_apa(x,d,N,P,w0,mu_max,epsilon,C1);%C1=2e-5 mse_vssapa = mse_vssapa + eVSSAPA.^2; for ii = 1:L msd_vssapa(1,ii) = msd_vssapa(1,ii) + norm(w(ii,:)-w_opt)/norm(w_opt); end [eVSSAPA1,w] = vss_apa(x,d,N,P,w0,mu_max,epsilon,C2);%C2=2e-4 mse_vssapa1 = mse_vssapa1 + eVSSAPA1.^2; for ii = 1:L msd_vssapa1(1,ii) = msd_vssapa1(1,ii) + norm(w(ii,:)-w_opt)/norm(w_opt); end [eVSSAPA2,w] = vss_apa(x,d,N,P,w0,mu_max,epsilon,C3);%C3=2e-6 mse_vssapa2 = mse_vssapa2 + eVSSAPA2.^2; for ii = 1:L msd_vssapa2(1,ii) = msd_vssapa2(1,ii) + norm(w(ii,:)-w_opt)/norm(w_opt); end end mse_apa = mse_apa/MCruns; mse_apa1 = mse_apa1/MCruns; mse_apa2 = mse_apa2/MCruns; mse_vssapa = mse_vssapa/MCruns; mse_vssapa1 = mse_vssapa1/MCruns; mse_vssapa2 = mse_vssapa2/MCruns; msd_apa = msd_apa/MCruns; msd_apa1 = msd_apa1/MCruns; msd_apa2 = msd_apa2/MCruns; msd_vssapa = msd_vssapa/MCruns; msd_vssapa1 = msd_vssapa1/MCruns; msd_vssapa2 = msd_vssapa2/MCruns; %% % MSE plot figure(1) plot(1:L,db(mse_apa/max(mse_apa)),'k-',... 1:L,db(mse_apa1/max(mse_apa1)),'b:',... 1:L,db(mse_apa2/max(mse_apa2)),'r-.',... 1:L,db(mse_vssapa/max(mse_vssapa)),'g-',... 1:L,db(mse_vssapa1/max(mse_vssapa1)),'c-.',... 1:L,db(mse_vssapa2/max(mse_vssapa2)),'m--'); xlabel('Number of iterationsa'); ylabel('MSE(dB)'); grid on; legend('standard APA(\mu=0.05)','standard APA(\mu=0.2)','standard APA(\mu=1)','VSS APA(C=1e-5)','VSS APA(C=1e-4)','VSS APA(C=1e-6)'); % MSD plot figure(2) plot(1:L,db(msd_apa/max(msd_apa)),'k-',... 1:L,db(msd_apa1/max(msd_apa1)),'b:',... 1:L,db(msd_apa2/max(msd_apa2)),'r-.',... 1:L,db(msd_vssapa/max(msd_vssapa)),'g-',... 1:L,db(msd_vssapa1/max(msd_vssapa1)),'c-.',... 1:L,db(msd_vssapa2/max(msd_vssapa2)),'m--'); xlabel('Number of iterations '); ylabel('MSD(dB)'); grid on; legend('standard APA(\mu=0.05)','standard APA(\mu=0.2)','standard APA(\mu=1)','VSS APA(C=1e-5)','VSS APA(C=1e-4)','VSS APA(C=1e-6)');