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Eigenstuff

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lightalone

PostPosted: Wed May 07, 2008 10:39 pm


So in my math class we're looking at eigenvalues, eigenvectors, eigenspaces and all that good stuff. And I was wondering if anybody knew any really killer applications for that. Mostly all we talk about in there are mass-spring systems, circuits, and things like that. But what else can they do?! They seem like a powerful tool and I'm really curious to know what I'm going to be able to do with them later.

Plus I think "Eigenvector" is about the most fun math word I've run across yet. Though I was a fan of the "multiplicative inverse property of equality" too!
PostPosted: Fri May 09, 2008 9:10 am


I think there are some very important applications of eigenvalues in engineering, but the ones that I know of are all in quantum mechanics and computer graphics. Actually, the Wikipedia page on eigenvectors has a short list of applications of this stuff. It *is* pretty kewl.

Swordmaster Dragon


zz1000zz

PostPosted: Sat May 17, 2008 1:53 am


The first thought to cross my mind when you said "killer application" was structural design of bridges. Several bridges are known to have collapsed (causing numerous deaths) due to oscillations being too close to their natural frequencies. To determine the natural frequency of a bridge, eigenvalues are used. In fact, structural engineering looks at eigenvalues a great deal, possibly more than any other field.

You see the "eigenstuff" applied in many different fields. Temperature reconstructions (through the use of PCA, which is used in many other fields), oil exploration, electrical systems, radio design, music theory and dozens more. Anything which involves frequencies can be expected to deal with "eigenstuff."
PostPosted: Wed Sep 10, 2008 3:27 am


Swordmaster Dragon
I think there are some very important applications of eigenvalues in engineering, but the ones that I know of are all in quantum mechanics and computer graphics. Actually, the Wikipedia page on eigenvectors has a short list of applications of this stuff. It *is* pretty kewl.


Indeed. The original paper by Page and Brin isn't much to get excited about, but check out the formula for pagerank through wikipedia. Though, note that they are computing a left-hand eigenvalue using the power method, and a formula from Matrix analysis called the Sherron-Morrison rank one update formula. I did my Math major senior research project on Pagerank last fall. Very interesting.

A good book on the topic is "Pagerank and Beyond" written by Meyer. He also wrote a graduate level textbook on Applied Linear Algebra and Matrix analysis which I have worn to death. Though is you want to understand the whole search process and the vector space model of search, you're going to need to look up the groundbreaking paper by Salton "A blueprint for automatic text indexing"

No_Data_Mining

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Mathematics

 
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