Error using linsolve: Matrix must be positive definite

Asked Apr 11 '18 at 12:21

Active Apr 11 '18 at 13:29

Viewed 779 times

I am trying to use compressed sensing for a 2D matrix. I am trying to run the following piece of code -

Nf=800;

N=401;

E=E(Nf,N);   %matrix of signal(this only for sampling) real matrix E is 2D matrix with size of Nf and N

% compressive sensing
M=ceil(0.3*N);
psi=fft(eye(N)); 
phi=randi(M,N);
EE = permute(E,[2 1]);
theta=phi*psi;
for k=1:Nf
y(:,k)=phi*EE(:,k);
 end

x0 = theta.'*y;
for p=1:Nf
X_hat(:,p) = l1eq_pd(x0(:,p), theta, [], y(:,p), 1e-5); %l1eq_pd=l1-magic
end
X1_hat=psi*X_hat;
XX_hat=permute(X1_hat,[2 1]);

but while running the code I get the following error.

Error using linsolve
Matrix must be positive definite.
Error in l1eq_pd (line 77)
[w, hcond] = linsolve(A*A', b, opts);

Error in simulation_mono_SAR (line 91)

X_hat(:,p) = l1eq_pd(x0(:,p), theta, [], y(:,p), 1e-5);

Could someone point me, what is the problem? Is it a problem inherent to l1-magic? shall I use another solver?

edited Apr 11 '18 at 13:29

asked Apr 11 '18 at 12:21

Neda

what is `l1eq_pd`? – Ander Biguri Apr 11 '18 at 12:59
This is the L1-magic (L-norm) – Neda Apr 11 '18 at 13:10
this https://statweb.stanford.edu/~candes/l1magic/ ? – Ander Biguri Apr 11 '18 at 13:12
The error comes from what `R` is, but you dont show it – Ander Biguri Apr 11 '18 at 13:14
I made mistake to type in the last line in the program, the R is not correct and I have edited my code. the code is as below. for p=1:Nf X_hat(:,p) = l1eq_pd(x0(:,p), theta, [], y(:,p), 1e-5); end – Neda Apr 11 '18 at 13:34
Ultimatelly, `theta*theta'` needs to be positive semi definite, and in your case it appears its not. – Ander Biguri Apr 12 '18 at 11:15
thanks so much for the answer, I will check it. – Neda Apr 13 '18 at 12:35

Error using linsolve: Matrix must be positive definite

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