It can also be shown: The rank of a matrix is equal to the number of its non-zero singular values. Confirm this for the following matrices: 0 0 1 0 A 0 1 0 0 1000 " B = 1 0 0 0 0100 0010 0001 0000 3 C (95).

Linear Algebra: A Modern Introduction
4th Edition
ISBN:9781285463247
Author:David Poole
Publisher:David Poole
Chapter4: Eigenvalues And Eigenvectors
Section4.1: Introduction To Eigenvalues And Eigenvectors
Problem 37EQ
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If A is a (rectangular) n × m matrix, it can be shown that the eigenvalues
of the symmetric square matrix AT A are non-negative. The singular values
01,02,...,0m of A are then defined to be the positive square roots of the
eigenvalues of AT A.
It can also be shown:
The rank of a matrix is equal to the number of its non-zero singular values.
Confirm this for the following matrices:
A =
D
-
0 0 1 0
0100
1000
1
1
1
B=
1 0 0 0
0100
0010
0001
0 000
C =
(13),
1
2 2
F-( 14 ) -(13)
E
=
F =
−1
0 0
Hint: The elementary unit vectors e; are the eigenvectors of a diagonal ma-
trix.
Transcribed Image Text:If A is a (rectangular) n × m matrix, it can be shown that the eigenvalues of the symmetric square matrix AT A are non-negative. The singular values 01,02,...,0m of A are then defined to be the positive square roots of the eigenvalues of AT A. It can also be shown: The rank of a matrix is equal to the number of its non-zero singular values. Confirm this for the following matrices: A = D - 0 0 1 0 0100 1000 1 1 1 B= 1 0 0 0 0100 0010 0001 0 000 C = (13), 1 2 2 F-( 14 ) -(13) E = F = −1 0 0 Hint: The elementary unit vectors e; are the eigenvectors of a diagonal ma- trix.
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