A singular value decomposition of a matrix A is as follows: 0.5 0.5 -0.5 -0.5] -0.5] [20 0 -0.5 0.5 0.5 -0.5 0 15 0.8 0.6 0.5 0.5 0.5 0.5 0 0 -0.6 0.8 -0.5 0.5 -0.5 0.5 0 0 (a) Find the closest (with respect to the Frobenius norm) matrix of rank 1 to A. A = A1 = (a) Find the Frobenius norm of A - A1. ||A-A1|| (c) Find the rank of A rank(A) =

Advanced Engineering Mathematics
10th Edition
ISBN:9780470458365
Author:Erwin Kreyszig
Publisher:Erwin Kreyszig
Chapter2: Second-order Linear Odes
Section: Chapter Questions
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A singular value decomposition of a matrix A is as follows:
0
0.5 0.5 -0.5 -0.5] [20
-0.5 0.5 0.5
-0.5 0 15 0.8 0.6
0 -0.6 0.8
0.5 0.5 0.5
0.5
0
-0.5 0.5 -0.5 0.5
0
0
(a) Find the closest (with respect to the Frobenius norm) matrix of rank 1 to A.
A =
A1 =
(a) Find the Frobenius norm of A - A1.
||A-A1||
(c) Find the rank of A
rank(A)
=
Transcribed Image Text:A singular value decomposition of a matrix A is as follows: 0 0.5 0.5 -0.5 -0.5] [20 -0.5 0.5 0.5 -0.5 0 15 0.8 0.6 0 -0.6 0.8 0.5 0.5 0.5 0.5 0 -0.5 0.5 -0.5 0.5 0 0 (a) Find the closest (with respect to the Frobenius norm) matrix of rank 1 to A. A = A1 = (a) Find the Frobenius norm of A - A1. ||A-A1|| (c) Find the rank of A rank(A) =
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