Can anyone please help me with the error in the code

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)')

[Supratik Das]

Error using /

Matrix dimensions must agree.

[Supratik Das]

please help

Answer 1

[Walter Roberson]

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.

[Supratik Das]

so how to solve this problem?

Answer 2

[Shayan Sepahvand]

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

[Supratik Das]

okay

[Supratik Das]

But i used covar and covm as functions which are called in the program, they have separate code.

covam.m and covar.m

[Walter Roberson]

We need to see the code for your covar.m then.

[Supratik Das]

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

[Supratik Das]

here it is please check