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Can anyone please help me with the error in the code

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Supratik Das
Supratik Das 2021-9-23
评论： Supratik Das 2021-9-23
clc, clear all, close all
d=sin(0.05*pi*(1:200)+2*pi*rand);
g=randn(1,200);
v1=filter(1,[1 -0.8],g);
v2=filter(1,[1 0.6],g);
x=d+v1;
figure(1)
plot(1:100,x(1:100),'b','linewidth',1.2)
hold on
plot(1:100,d(1:100),'r','linewidth',1.2)
grid on
xlabel('n')
legend('x(n)','d(n)')
title('plot of x(n) and d(n)')
figure(2)
plot(1:100,v2(1:100),'b','linewidth',1.2)
grid on
xlabel('n')
title('plot of v_2(n)')
Rv2=covar(v2,4);
figure(3)
stem(Rv2,'b','linewidth',1.2)
grid on
xlabel('k')
title('autocorrelation of v_2(n)')
rxv2=convm(x,4)'*convm(v2,4)/(length(x)-1);
figure(4)
stem(rxv2,'b','linewidth',1.2)
grid on
xlabel('k')
title('cross-correlation between x(n) and v_2(n)')
w=rxv2(1,:)/Rv2;
v1hat=filter(w,1,v2);
dhat=x-v1hat;
figure(5)
plot(dhat(1:100))
hold on
plot(d(1:100),'r')
xlabel('n')
title('Estimated d(n) vs actual d(n)')
legend('Estimate d(n)', 'Actual d(n)')

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回答（2 个）

Walter Roberson
Walter Roberson 2021-9-23
Ran in:
clc, clear all, close all
d=sin(0.05*pi*(1:200)+2*pi*rand);
g=randn(1,200);
v1=filter(1,[1 -0.8],g);
v2=filter(1,[1 0.6],g);
x=d+v1;
figure(1)
plot(1:100,x(1:100),'b','linewidth',1.2)
hold on
plot(1:100,d(1:100),'r','linewidth',1.2)
grid on
xlabel('n')
legend('x(n)','d(n)')
title('plot of x(n) and d(n)')
figure(2)
plot(1:100,v2(1:100),'b','linewidth',1.2)
grid on
xlabel('n')
title('plot of v_2(n)')
Rv2=covar(v2,4);
ans = 1×2
204 5
size(Rv2)
ans = 1×2
5 5
figure(3)
stem(Rv2,'b','linewidth',1.2)
grid on
xlabel('k')
title('autocorrelation of v_2(n)')
cmx = convm(x,4);
cmv2 = convm(v2,4);
rxv2 = cmx'*cmv2/(length(x)-1);
size(cmx), size(cmv2), size(rxv2)
ans = 1×2
203 4
ans = 1×2
203 4
ans = 1×2
4 4
figure(4)
stem(rxv2,'b','linewidth',1.2)
grid on
xlabel('k')
title('cross-correlation between x(n) and v_2(n)')
size(rxv2), size(Rv2)
ans = 1×2
4 4
ans = 1×2
5 5
w=rxv2(1,:)/Rv2;
Error using /
Matrix dimensions must agree.
v1hat=filter(w,1,v2);
dhat=x-v1hat;
figure(5)
plot(dhat(1:100))
hold on
plot(d(1:100),'r')
xlabel('n')
title('Estimated d(n) vs actual d(n)')
legend('Estimate d(n)', 'Actual d(n)')
function R = covar(x,p)
%
% This function sets up a covariance matrix
%
x = x(:);
m = length(x);
x = x - ones(m,1)*(sum(x)/m);
cm = convm(x,p+1);
size(cm)
R = cm'*cm/(m-1);
end
function X = convm(x,p)
%
% This function sets up a convolution matrix
%
N = length(x)+2*p-2;
x = x(:);
xpad = [zeros(p-1,1);x;zeros(p-1,1)];
for i=1:p
X(:,i)=xpad(p-i+1:N-i+1);
end
end
What is happening is that you are creating one of your variables by calling covar(), which adds 1 to the second parameter (4) to get the size -- so it will be something by 5. But the other variable you get by calling convm(), which does not add 1 to the second parameter (4), so it will be something by 4. The 5 and 4 then become incompatible sizes.
Shayan Sepahvand
Shayan Sepahvand 2021-9-23
Hi,
the first argument of
covar(sys, w)
should be some LTI system (discrete in your case), I suggest you to first derive the LTI form of v2 using z transform, then use covar
good luck
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Supratik Das
Supratik Das 2021-9-23
for covar.m
function R = covar(x,p)
%
% This function sets up a covariance matrix
%
x = x(:);
m = length(x);
x = x - ones(m,1)*(sum(x)/m);
R = convm(x,p+1)'*convm(x,p+1)/(m-1);
end
for covm.m
function X = convm(x,p)
%
% This function sets up a convolution matrix
%
N = length(x)+2*p-2;
x = x(:);
xpad = [zeros(p-1,1);x;zeros(p-1,1)];
for i=1:p
X(:,i)=xpad(p-i+1:N-i+1);
end

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