17. If A is invertible, then the columns of A¹ are linearly independent. Explain why.

Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
Problem 1PE
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Question
17
2.3 EXERCISES
Unless otherwise specified, assume that all matrices in these
exercises are n xn. Determine which of the matrices in Exercises
1-10 are invertible. Use as few calculations as possible. Justify
your answers,
12.
1.
3.
5.
7.
[33]
-6
5
-3
8
-1
3
-2
0
9. [M]
PARTE
0
0
1
notboos 930
-4
4
-6
-1
10. [M] 7
9
8
7
-7 0
5
3
bi bilo 2.
0
-9
MOGENS
0
9
-1
-3
30
5
8
-6 3
-1 2
-5
0
1
mom
2
7
4.
til al
-3
2
1
of 6.
8.
-4 6
6
-9
-7
1 -5
0
3
-3
6
1
0
0
0
30
20
0
4
11
9
-1
-7 -7
11
9
-5 10
19
2
3
-1 bis bud
-4
4
0
3 7 47
47
5 9
0 2
00
6
6
81
10 in
01
100 7
5 3
97.des the
642
-8 igib to odman od
53
9
hoqon biss
6 4 -9 1-5 to bolą ni beau
5 2 11
8
10
4
(1) JA
In Exercises 11 and 12, the matrices are all n xn. Each part of
the exercises is an implication of the form "If "statement 1",
then "statement 2"." Mark an implication as True if the truth of
"statement 2" always follows whenever "statement 1" happens
to be true. An implication is False if there is an instance in
which "statement 2" is false but "statement 1" is true. Justify each
answer.
11 a. If the equation Ax = 0 has only the trivial solution, then
A is row equivalent to the n x n identity matrix.
b. If the columns of A span R", then the columns are linearly
independent.
c. If A is an n x n matrix, then the equation Ax = b has at
least one solution for each b in R".
SA
d. If the equation Ax = 0 has a nontrivial solution, then A
has fewer than n pivot positions.
e. If AT is not invertible, then A is not invertible.
les as
c. If the equation Ax = b has at least one solution for each
b in R", then the solution is unique for each b.
2.3 Characterizations of Invertible Matrices 117
13. An mxn upper triangular matrix is one whose entries
below the main diagonal are 0's (as in Exercise 8). When
is a square upper triangular matrix invertible? Justify your
answer.
14. An mxn lower triangular matrix is one whose entries
above the main diagonal are 0's (as in Exercise 3). When
is a square lower triangular matrix invertible? Justify your
answer.
d. If the linear transformation (x)→ Ax maps R" into R",
then A has n pivot positions.
e. If there is a b in R" such that the equation Ax=b is
inconsistent, then the transformation x→ Ax is not one-
to-one.
15. Can a square matrix with two identical columns be invert-
ible? Why or why not?
16. Is it possible for a 5 x 5 matrix to be invertible when its
columns do not span R5? Why or why not? (S) (1)
17. If A is invertible, then the columns of A are linearly
independent. Explain why.
18. If C is 6 x 6 and the equation Cx= v is consistent for every
v in R6, is it possible that for some v, the equation Cx = v
has more than one solution? Why or why not?
aocvdo bi
19. If the columns of a 7 x 7 matrix D are linearly independent,
what can you say about solutions of Dx = b? Why?
20. If n x n matrices E and F have the property that EF = 1,
then E and F commute. Explain why.
21. If the equation Gx = y has more than one solution for some
noiy in R", can the columns of G span R"? Why or why not?
22. If the equation Hx = c is inconsistent for some e in R", what
can you say about the equation Hx = 0? Why?
23. If an n x n matrix K cannot be row reduced to I, what can
you say about the columns of K? Why?
24. If L is n x n and the equation Lx = 0 has the trivial solution,
do the columns of L span R"? Why?
28.
If there is an n x n matrix D such that AD = I, then there
is also an n x n matrix C such that CA = I.
1809 BOITO 28. Sh
b. If the columns of A are linearly independent, then the
columns of A span R".
25. Verify the boxed statement preceding Example 1.
26. Explain why the columns of A2 span R" whenever the
(columns of A are linearly independent.
29.
27. Show that if AB is invertible, so is A. You cannot use Theorem
6(b), because you cannot assume that A and B are invertible.
[Hint: There is a matrix W such that ABW = I. Why?]
Show that if AB is invertible, so is B.
If A is an n x n matrix and the equation Ax=b has more than
one solution for some b, then the transformation x→ Ax is
not one-to-one. What else can you say about this transforma-
tion? Justify your answer.
Transcribed Image Text:2.3 EXERCISES Unless otherwise specified, assume that all matrices in these exercises are n xn. Determine which of the matrices in Exercises 1-10 are invertible. Use as few calculations as possible. Justify your answers, 12. 1. 3. 5. 7. [33] -6 5 -3 8 -1 3 -2 0 9. [M] PARTE 0 0 1 notboos 930 -4 4 -6 -1 10. [M] 7 9 8 7 -7 0 5 3 bi bilo 2. 0 -9 MOGENS 0 9 -1 -3 30 5 8 -6 3 -1 2 -5 0 1 mom 2 7 4. til al -3 2 1 of 6. 8. -4 6 6 -9 -7 1 -5 0 3 -3 6 1 0 0 0 30 20 0 4 11 9 -1 -7 -7 11 9 -5 10 19 2 3 -1 bis bud -4 4 0 3 7 47 47 5 9 0 2 00 6 6 81 10 in 01 100 7 5 3 97.des the 642 -8 igib to odman od 53 9 hoqon biss 6 4 -9 1-5 to bolą ni beau 5 2 11 8 10 4 (1) JA In Exercises 11 and 12, the matrices are all n xn. Each part of the exercises is an implication of the form "If "statement 1", then "statement 2"." Mark an implication as True if the truth of "statement 2" always follows whenever "statement 1" happens to be true. An implication is False if there is an instance in which "statement 2" is false but "statement 1" is true. Justify each answer. 11 a. If the equation Ax = 0 has only the trivial solution, then A is row equivalent to the n x n identity matrix. b. If the columns of A span R", then the columns are linearly independent. c. If A is an n x n matrix, then the equation Ax = b has at least one solution for each b in R". SA d. If the equation Ax = 0 has a nontrivial solution, then A has fewer than n pivot positions. e. If AT is not invertible, then A is not invertible. les as c. If the equation Ax = b has at least one solution for each b in R", then the solution is unique for each b. 2.3 Characterizations of Invertible Matrices 117 13. An mxn upper triangular matrix is one whose entries below the main diagonal are 0's (as in Exercise 8). When is a square upper triangular matrix invertible? Justify your answer. 14. An mxn lower triangular matrix is one whose entries above the main diagonal are 0's (as in Exercise 3). When is a square lower triangular matrix invertible? Justify your answer. d. If the linear transformation (x)→ Ax maps R" into R", then A has n pivot positions. e. If there is a b in R" such that the equation Ax=b is inconsistent, then the transformation x→ Ax is not one- to-one. 15. Can a square matrix with two identical columns be invert- ible? Why or why not? 16. Is it possible for a 5 x 5 matrix to be invertible when its columns do not span R5? Why or why not? (S) (1) 17. If A is invertible, then the columns of A are linearly independent. Explain why. 18. If C is 6 x 6 and the equation Cx= v is consistent for every v in R6, is it possible that for some v, the equation Cx = v has more than one solution? Why or why not? aocvdo bi 19. If the columns of a 7 x 7 matrix D are linearly independent, what can you say about solutions of Dx = b? Why? 20. If n x n matrices E and F have the property that EF = 1, then E and F commute. Explain why. 21. If the equation Gx = y has more than one solution for some noiy in R", can the columns of G span R"? Why or why not? 22. If the equation Hx = c is inconsistent for some e in R", what can you say about the equation Hx = 0? Why? 23. If an n x n matrix K cannot be row reduced to I, what can you say about the columns of K? Why? 24. If L is n x n and the equation Lx = 0 has the trivial solution, do the columns of L span R"? Why? 28. If there is an n x n matrix D such that AD = I, then there is also an n x n matrix C such that CA = I. 1809 BOITO 28. Sh b. If the columns of A are linearly independent, then the columns of A span R". 25. Verify the boxed statement preceding Example 1. 26. Explain why the columns of A2 span R" whenever the (columns of A are linearly independent. 29. 27. Show that if AB is invertible, so is A. You cannot use Theorem 6(b), because you cannot assume that A and B are invertible. [Hint: There is a matrix W such that ABW = I. Why?] Show that if AB is invertible, so is B. If A is an n x n matrix and the equation Ax=b has more than one solution for some b, then the transformation x→ Ax is not one-to-one. What else can you say about this transforma- tion? Justify your answer.
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