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From: "Hua Wang" <ehwang@163.com>
Newsgroups: comp.soft-sys.matlab
Subject: how to deal with the inversion problem of a huge sparse covariance matrix
Date: Sat, 26 Sep 2009 18:16:07 +0000 (UTC)
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Dear All,

I am processing some data using weighted least-squares (WLS) method. As you know, the solution of a system function A*x=b with weighting matrix P is that: x=inv(A'*P*A)*(A'*P*b);

I am solving the system function using Cholesky decomposition. The formula is:
w=cholinc(P,'0');
x=(w*A)\(w*b);

I am not sure whether the above method is possible for the back slash operator. But first of all, I met the problem of calculating weight matrix P from the covariance matrix C, i.e. P=inv(C). It is almost impossible to get the inverse of the huge sparse matrix C.

Could anybody give me some suggestions to solve such equation A*x=B, giving huge sparse covariance matrix C? It is urgent for me!

Thanks in advance!

Hua