Can anyone help me?

[[email protected]]

Can anyone help me?

I am currently doing research on sparseness matrix issues. As I am
carrying on this topic, I had a problem that don't know what to do.
Basically the problem is as follows:


A and B are originally both sparse matrix, and I have to calcuate
P=(inv(B)*A)^(-2), when the order of P is small say 32 by 32, I still
can apply P into my algorithm and find a good solution, but when the
order is large, say 72 by 72 , and I applied it in Matlab@, I got a
warning like below


Warning: Matrix is close to singular or badly scaled.
Results may be inaccurate. RCOND = 2.781682e-021.


If the order of A and B are larger, say 1000 by 1000, then my system is

just not responding at all no matter how long I wait and matlab is
switch off automatically.


Can anyone help me to find a way slove the P matrix in large sparse
case in Matlab, which can avoid the matrix becomes singular?
Many thanks.


Khan.

 

[[email protected]]

Can anyone help me?

Yes we can. Esp when the subject says nothing about the problem. And only
about your needs. State your problem in the subject. Besides that a math
group is proberbly better.

I am currently doing research on sparseness matrix issues. As I am
carrying on this topic, I had a problem that don't know what to do.
Basically the problem is as follows:

A and B are originally both sparse matrix, and I have to calcuate
P=(inv(B)*A)^(-2), when the order of P is small say 32 by 32, I still
can apply P into my algorithm and find a good solution, but when the
order is large, say 72 by 72 , and I applied it in Matlab@, I got a
warning like below

Warning: Matrix is close to singular or badly scaled.
Results may be inaccurate. RCOND = 2.781682e-021.

If the order of A and B are larger, say 1000 by 1000, then my system is

just not responding at all no matter how long I wait and matlab is
switch off automatically.

Bad programming on matlabs part then (good programs handle overload..).

Can anyone help me to find a way slove the P matrix in large sparse
case in Matlab, which can avoid the matrix becomes singular?
Many thanks.

Quick route to solution. Implement your functions inv() mult() etc.. in C.
Run it on a decent unix machine. Alternative use bigiron for matlab =)

 

[Greg Neill]

Can anyone help me to find a way slove the P matrix in large sparse
case in Matlab, which can avoid the matrix becomes singular?
Many thanks.

Why don't you try posting your question in
sci.math.symbolic?