Homework Assignment for Math 477: Singular Value Decomposition, Assignments of Linear Algebra

A homework assignment for a math 477 course, which covers singular value decomposition (svd). The assignment includes problems on determining svds of various matrices, finding the minimum and maximum singular values of a matrix, and finding the orthogonal projector onto the range of a matrix. The assignment also includes a proof and a geometric interpretation of a statement about orthogonal projectors and unitary matrices.

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Pre 2010

Uploaded on 08/16/2009

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Math 477 Homework Assignment 2, due Sept.28, 2006
1. Determine SVDs of the following matrices. Do not use a computer, and do not use the method
for hand calculations discussed in class. Use only basic properties of the SVD and note that the
matrices are either diagonal matrices or rank-1 matrices:
(a) 3 0
02,(b) 2 0
0 3 ,(c)
0 2
0 0
0 0
,(d) 1 1
0 0 ,(e) 1 1
1 1 .
2. In the discussion of matrix norms we claimed that the 2-norm of the matrix
A=1 1
0 1
is approximately 1.6180. Using the SVD, work out (the “by-hand” method is from now on
allowed) the exact values of σmin(A) and σmax(A) for this matrix.
3. Find the SVDs of the following matrices:
A=
400
000
007
000
, B =2 1 , C =5
4.
4. If Pis an orthogonal projector, then I2Pis unitary. Prove this algebraically, and give a
geometric interpretation.
5. Consider the matrices
A=
1 0
0 1
1 0
, B =
1 2
0 1
1 0
.
Answer the following questions by hand calculation.
(a) What us the orthogonal projector Ponto range(A), and what is the image under Pof the
vector [1,2,3]?
(b) Same questions for B.

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Math 477 — Homework Assignment 2, due Sept.28, 2006

  1. Determine SVDs of the following matrices. Do not use a computer, and do not use the method for hand calculations discussed in class. Use only basic properties of the SVD and note that the matrices are either diagonal matrices or rank-1 matrices:

(a)

[

]

, (b)

[

]

, (c)

 (^) , (d)

[

]

, (e)

[

]

  1. In the discussion of matrix norms we claimed that the 2-norm of the matrix

A =

[

]

is approximately 1.6180. Using the SVD, work out (the “by-hand” method is from now on allowed) the exact values of σmin(A) and σmax(A) for this matrix.

  1. Find the SVDs of the following matrices:

A =

 ,^ B^ =^

[

]

, C =

[

]

  1. If P is an orthogonal projector, then I − 2 P is unitary. Prove this algebraically, and give a geometric interpretation.
  2. Consider the matrices

A =

 , B =

Answer the following questions by hand calculation.

(a) What us the orthogonal projector P onto range(A), and what is the image under P of the vector [1, 2 , 3]∗? (b) Same questions for B.