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From: Rune Allnor <allnor@tele.ntnu.no>
Newsgroups: comp.soft-sys.matlab
Subject: Re: how to deal with the inversion problem of a huge sparse
Date: Mon, 28 Sep 2009 02:24:06 -0700 (PDT)
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On 28 Sep, 11:19, "Hua Wang" <ehw...@163.com> wrote:
> > I haven't seen anything that indicates neither the size of
> > these images in terms of pixels, or the dimensions of the
> > covarinance matrices. Nor have I seen anything to indicate
> > what the purpose of the analysis is.
>
> Sorry that I forgot the pixel size. In my dataset, the original pixel size is about 90 m. It is to slow to process such high resolution data. After multilooking (i.e. average for the neighbor pixels), the pixel size is about 360 m. So there are about 300*2400 pixels for each image. After removing some pixels with NaN values, the dimension of the final covariance matrix is about 40,000 by 40,000 with 15 million non-zeros.

The numbers alone go a very long way to indicate that the
problem statement is almost certainly wrong.

Rune