Inverse of matrix is wrong?

조회 수: 6 (최근 30일)
Shayma Al Ali
Shayma Al Ali 2021년 11월 3일
답변: the cyclist 2021년 11월 3일
I have a 583x583 matrix called "F". I am trying to use F to get a variable X for an equation FX=B. However, when I solve for X, the results do not seem correct and have negative values. When looking at the matrix F, I noticed that both codes:
X=inv(F)*B and X=F\B
yield the same results. However, I don't think that the inverse of F is correct beacuse when I multiply F by inv(F), I do not get the identity matrix. What could be the possible result of that?
The code used to construct the matrix F:
val=zeros(1,583);
j=[10,10E-1,10E-2,(9:-1:1)*(10^-3)];
val(1:12)=j;
sum_val=sum(val_norm); val_norm=val/sum_val; %normalize the function
F=toeplitz(val_norm,[val_norm(1), zeros(1,numel(val_norm)-1 )]);
and to check that X=inv(F)*B and X=F\B are the same
B=rand(583,1);
X1=inv(F)*B
X2=F\B
  댓글 수: 2
the cyclist
the cyclist 2021년 11월 3일
Your code to create F gives an error:
val=zeros(1,583);
j=[10,10E-1,10E-2,(9:-1:1)*(10^-3)];
val(1:12)=j;
sum_val=sum(val_norm); val_norm=val/sum_val; %normalize the function
Unrecognized function or variable 'val_norm'.
F=toeplitz(val_norm,[val_norm(1), zeros(1,numel(val_norm)-1 )]);
I can think of ways to fix it, but I dont want to inadvertently create a different value of F than you are.
Shayma Al Ali
Shayma Al Ali 2021년 11월 3일
편집: Shayma Al Ali 2021년 11월 3일
Sorry it should be like this:
val=zeros(1,583);
j=[10,10E-1,10E-2,(9:-1:1)*(10^-3)];
val(1:12)=j;
sum_val=sum(val); val_norm=val/sum_val; %normalize the function
F=toeplitz(val_norm,[val_norm(1), zeros(1,numel(val_norm)-1 )]);

댓글을 달려면 로그인하십시오.

답변 (1개)

the cyclist
the cyclist 2021년 11월 3일
Looks fine to me:
val=zeros(1,583);
j=[10,10E-1,10E-2,(9:-1:1)*(10^-3)];
val(1:12)=j;
sum_val=sum(val); val_norm=val/sum_val; %normalize the function
F=toeplitz(val_norm,[val_norm(1), zeros(1,numel(val_norm)-1 )]);
shouldBeIdentityMatrix = F*inv(F);
identityMatrix = eye(583);
maxError = max(abs(shouldBeIdentityMatrix(:)-identityMatrix(:)))
maxError = 1.1102e-16
The maximum error between the calculated identity matrix F*inv(F) and the theoretical identify matrix is of the order of computational roundoff error.

카테고리

Help CenterFile Exchange에서 Linear Algebra에 대해 자세히 알아보기

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by