Talk:Lanczos algorithm

[[1]] - an unfocused variety of Lanczos algorithm —Preceding unsigned comment added by 134.219.166.104 (talk • contribs) 21:23, 1 September 2005

This doesn't have much but it does have a reference to a book mathworld on Lanczos Algorithm]—Preceding unsigned comment added by RJFJR (talk • contribs) 23:36, 25 September 2005

I don't believe this is the Lanczos algorithm at all. It is the power method. —Preceding unsigned comment added by 130.126.55.123 (talk • contribs) 01:04, 5 August 2006

I don't know if the algorithm is correct, but it's certainly different than the power method, and presented pretty clearly. I think it's gotten me on the right track at least... Thanks. --Jjdonald (talk) 22:22, 17 December 2007 (UTC)[reply]

It is not easy to say it's wrong or correct, since quite some information is missing in order to apply it: (a) how to choose v[1], (b) how to chose m, (c) how to recognize the eigenvalues of A among those of T_mm. Unfortunately, this vagueness is by no means eliminated by the Numerical stability section. — MFH:Talk 21:57, 12 September 2008 (UTC)[reply]

It should state that "it applies to Hermitian matrices" at the start of the article and not somewhere in the middle. limweizhong (talk) 09:54, 11 November 2008 (UTC)[reply]

In Latent Semantic Indexing, for...

I really think that this sentense has nothing to do in the first paragraph! Please someone who understand anything about it should create a separate section and explain what this is about! —Preceding unsigned comment added by Alain Michaud (talk • contribs) 16:37, 19 February 2010 (UTC)[reply]

Extracting information from tridiagonal matrix

So Lanczos gives you a tridiagonal matrix. I think a link would be helpful which explains how to extract low eigenvalues/eigenvectors from this matrix. —Preceding unsigned comment added by 209.6.144.249 (talk) 06:30, 2 March 2008 (UTC)[reply]

Agree - or largest eigenvalues: anyway, the article starts by saying that it's for calculating eigenvalues, but then stops with the tridiag. matrix.

B.t.w., the algorithm calculates up to v[m+1], I think this could be avoided. (also, "unrolling" the 1st part of the m=1 case as initialization should allow to avoid using v[0].) — MFH:Talk 03:09, 11 September 2008 (UTC)[reply]

PS: also, it should be said what is 'm'...