Large scale generalized eigenvalue problem involving dense symmetric positive-definite matrices
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Hi all,
I need to solve a generalized eigenvalue problem [A][x]=[B][x][lambda]; where [A] and [B] are positive definite matrices and the resulting [x] should be normalised as [x'][B][x]=[I]; [I] = Identity matrix.
Uptil now, I was using the following commands to solve the problem on a 32-bit computer satisfactorily
L = chol(B);
CL = (inv(L))*A*(inv(L))';
make_mswindows
[v1,r1] = syev(CL,'qr');
eigvector = (inv(L))'*v1;
eigvalue = sqrt(r1);
Here, syev is a function from the MATLAB wrapper for LAPACK (available at <ftp://ftp.netlib.org/lapack/lapwrapmw/index.html>).
But now that I have switched over to a 64-bit workstation, I am getting NO COMPILER error. I reckon that I have to make changes in the mex-code files which I am not able to do.
Is there any other way to this problem? Can we solve the generalized eigenvalue problem by any other method, efficiently. It should be noted that the size of matrices A and B is quite big (200-800 and even more).
Regards, N. Madani SYED
1 comentario
Walter Roberson
el 23 de Dic. de 2011
When you say you are getting "NO COMPILER" error, do you mean that you are getting an error indicating that you have not set up a compiler, or do you mean that the code compiles without error message?
Respuesta aceptada
Más respuestas (1)
Andrew Newell
el 23 de Dic. de 2011
You could use eig in place of syev. Or, if you don't need the normalization, you could solve the generalized eigenvalue problem directly using
[eigvector,eigvalue] = eig(A,B)
2 comentarios
N Madani SYED
el 25 de Dic. de 2011
Andrew Newell
el 25 de Dic. de 2011
That leaves using eig in place of syev.
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