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A Singularly Valuable Decomposition: The SVD of a Matrix

First Paragraph: Every teacher of linear algebra should be familiar with the matrix singular value decomposition (or SVD). It has interesting and attractive algebraic properties, and conveys important geometrical and theoretical insights about linear transformations. The close connection between the SVD and the well-known theory of diagonalization for symmetric matrices makes the topic immediately accessible to linear algebra teachers and, indeed, a natural extension of what these teachers already know. At the same time, the SVD has fundamental importance in several different applications of linear algebra.

Identifier: 
http://www.math.umn.edu/~lerman/math5467/svd.pdf
Subject: 
Rating: 
Average: 4 (1 vote)
Creator(s): 
Dan Kalman
Cataloger: 
Daniel Drucker
Publisher: 
The College Mathematics Journal 27 No. 1 (1996), 2–23
Rights: 
Dan Kalman

Comments

drucker@math.wayne.edu's picture

HIghly readable and thorough discussion of the SVD, aimed at a general audience.

meade's picture

Well-written introduction to the SVD, emphasizing both theory and application. Closely follows the presentation popularized by Strang. Biggest objection is the statement that the SVD "is probably not feasible to include the SVD in the first linear algebra course".

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