信号处理基础 何子述版 第四章仿真题(共10页)

1、第 页S140101217 张书畅4.17function E P P1=lms2(mu)sigma_v1_2=0.27;b(1)=-0.8458;b(2)=0.9458;a(1)=-(b(1)+b(2);a(2)=b(1)*b(2);datlen=500;P=zeros(2,datlen);E=zeros(1,datlen);for i=1:datlen rand(state,sum(100*clock); s=sqrt(sigma_v1_2)*randn(datlen,1); x=filter(1,1,a,s); sigma_v2_2=0.1; u=x+sqrt(sigma_v2_2)*r

2、andn(datlen,1); d=filter(1,1,-b(1),s); w0=1;0; w=w0; M=length(w0); N=length(u); for n=M:N u1=u(n:-1:n-M+1); y(n)=w*u1; e(n)=d(n)-y(n); w=w+mu*conj(e(n)*u1; P1(:,n)=w; end P=P+P1; E=E+e.2;endendE1 P1 P11=lms2(0.015);E2 P2 P12=lms2(0.025);E3 P3 P13=lms2(0.05);g=500;figure(1);plot(conj(E1)/g);hold on;p

3、lot(conj(E2)/g);hold on;plot(conj(E3)/g);xlabel(迭代(di di)次数);ylabel(MSE);title(学习曲线);figure(2);plot(conj(P1)/g);hold on;plot(conj(P11);xlabel(迭代(di di)次数);ylabel(权值);title(步长为0.015);figure(3);plot(conj(P2)/g);hold on;plot(conj(P12);xlabel(迭代(di di)次数);ylabel(权值);title(步长为0.025);figure(4);plot(conj(P

4、3)/g);hold on;plot(conj(P13);xlabel(迭代(di di)次数);ylabel(权值);title(步长为0.05); 4.18data_len=512;trials=100;n=1:data_len;a1=-0.975;a2=0.95;sigma_v_2=0.0731;error1=zeros(data_len,1);error2=zeros(data_len,1);weight1=zeros(2,data_len);weight2=zeros(2,data_len);for loop=1:100 v=sqrt(sigma_v_2)*randn(data_le

5、n,1,trials); u0=0 0; num=1; den=1 a1 a2; Zi=filtic(num,den,u0); u=filter(num,den,v,Zi); mu1=0.05; mu2=0.005; w1=zeros(2,data_len); w2=zeros(2,data_len); e1=zeros(data_len,1); e2=zeros(data_len,1); d1=zeros(data_len,1); d2=zeros(data_len,1); for n=3:data_len-1 w1(:,n+1)=w1(:,n)+mu1*u(n-1:-1:n-2,:,1)*

6、conj(e1(n); w2(:,n+1)=w2(:,n)+mu2*u(n-1:-1:n-2,:,1)*conj(e2(n); d1(n+1)=w1(:,n+1)*u(n:-1:n-1,:,1); d2(n+1)=w2(:,n+1)*u(n:-1:n-1,:,1); e1(n+1)=u(n+1,1)-d1(n+1); e2(n+1)=u(n+1,1)-d2(n+1); end error1=error1+e1.2; error2=error2+e2.2; weight1=weight1+w1; weight2=weight2+w2; enderror1=error1./100; error2=

7、error2./100; weight1=weight1./100; weight2=weight2./100; figure(1); plot(w1(1,:);hold on; plot(w1(2,:);hold on; plot(weight1(1,:);hold on; plot(weight1(2,:); title(步长为0.05时权向量(xingling)收敛曲线); xlabel(迭代(di di)次数);ylabel(权向量(xingling);figure(2); plot(w2(1,:);hold on;plot(w2(2,:);hold on; plot(weight2(

8、1,:);hold on; plot(weight2(2,:); title(步长为0.005时权向量收敛曲线); xlabel(迭代次数);ylabel(权向量);N=1:data_len;figure(3);plot(N,error1,*,N,error2);title(步长分别为0.05和0.005时100次独立实验的学习曲线);legend(mu1=0.05,mu2=0.005);xlabel(迭代次数);ylabel(均方误差);wopt=zeros(2,trials);Jmin=zeros(1,trials);sum_eig=zeros(trials,1);for m=1:tria

9、ls rm=xcorr(u(:,:,m),biased); R=rm(512),rm(513);rm(511),rm(512); p=rm(511);rm(510); wopt(:,m)=Rp; v,d=eig(R); Jmin(m)=rm(512)-p*wopt(:,m); sum_eig(m)=d(1,1)+d(2,2);ende1_100trials_ave=0.01*sum(sum_eig);e2_100trials_ave=0.01*sum(sum_eig);sJmin=sum(Jmin)/trials;Jex1=e1_100trials_ave-sJmin;Jex2=e2_100t

10、rials_ave-sJmin;sum_eig_100trials=sum(sum_eig)/100;Jexfin=mu1*sJmin*(sum_eig_100trials/(2-mu1*sum_eig_100trials);Jexfin2=mu2*sJmin*(sum_eig_100trials/(2-mu2*sum_eig_100trials);M1=Jexfin/sJminM2=Jexfin2/sJmin M1 = 0.0048 M2 = 0.0502 4.19clear alltrials=100;data_len=1000;n=1:data_len;A1=zeros(data_len

11、,2);EA1=zeros(data_len,1);for i=1:trials; sigma_v_2=0.5; phi=2*pi*rand(1,1); signal=sin(pi/2*n+phi); u=signal+sqrt(sigma_v_2)*randn(data_len,1); d=2*cos(pi/2*n+phi); mu=0.015; M=2; w=zeros(M,data_len); e=zeros(data_len,1); y=zeros(data_len,1); for m=2:data_len-1 w(:,m+1)=w(:,m)+mu*u(m:-1:m-1)*conj(e

12、(m); y(m+1)=w(:,m+1)*u(m+1:-1:m); e(m+1)=d(m+1)-y(m+1); end A1=A1+conj(w); EA1=EA1+e.2;endfigure(1);plot(e.2);xlabel(迭代(di di)次数);ylabel(均方误差(wch);title(单次实验(shyn)学习曲线);figure(2);plot(EA1/trials);xlabel(迭代次数);ylabel(均方误差);title(100次实验学习曲线);figure(3);plot(A1/trials);hold on;plot(conj(w);xlabel(迭代次数);ylabel(权向量);title(权向量收敛曲线); 内容总结（1）S14010