Elementary Matrices and Their Inverses: Solutions for Math 110, Fall 2006, Assignments of Linear Algebra

Solutions to homework problems related to elementary matrices and their inverses for math 110, fall 2006. It covers topics such as finding the inverses of elementary matrices, their symmetry, and the rank of a matrix. Problems include determining the inverses of specific elementary matrices and analyzing the invertibility of certain matrices.

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Pre 2010

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Solutions to Homework 7.
Math 110, Fall 2006.
Prob 3.1.3. To find the inverses of the elementary matrices, we must simply undo the corresponding
elementary operations:
(a)
001
010
100
,(b)
100
0 1/3 0
001
,(c)
100
010
201
.
Prob 3.1.5. If Eis an elementary matrix of type I corresponding to the swap or rows iand J, then E
has 1 in positions (i, j) and (j, i), zeros in positions (i, i) and (j, j), and the other entries exactly as in the
identity matrix of the appropriate size. But then Eis symmetric, i.e., its transpose is Eitself. Likewise, if
Eis of type II, then its transpose is itself. If Eis of type III and corresponds to adding row jmultiplied by
cto row i, then it looks like the identity matrix except for the entry cin position (i, j). Then its transpose
has cin position (j, i), which corresponds to adding row imultiplied by cto row j.
So, in all three cases Eis an elementary matrix if and only if so is Et.
Prob 3.2.2. (a) 2, (b) 3, (c) 2, (d) 1, (e) 3, (f) 3, (g) 1.
Prob 3.2.6.
(a) Tis invertible. Writing the matrix of Tin the standard basis for P2(IR) and inverting it, we get
T1(ax2+bx +c) = ax2(4a+b)x(10a+ 2b+c).
(b) Tis not invertible, since it has a nontrivial kernel, for example, T1 = 0.
(c) Tis invertible: the same approach as in (a) yields
T1(a, b, c) = 1
6a1
3b+1
2c, 1
2a1
2c, 1
6a+1
3b+1
2c.
(d) Representing Twith respect to the standard bases for IR3and P2(IR) and inverting the obtained matrix,
we get
T1(a+bx +cx2) = (c, (ab)/2,(a+b2c)/2).
(e) Tis invertible, and
T1(a, b, c) = 1
2ab+1
2cx2+1
2a+1
2cx+b.
(f) Tis not invertible: for example, the matrix
A=11
1 1
is in the kernel of T, since both tr(A) and tr(EA) are zero, and the other two traces are also zero since
tr(At) = tr(A) and tr(EA) = tr(AE) always.
Prob 3.2.8. Since cA = (cI)Aand since the matrix cI is invertible for c6= 0, we conclude that multipli-
cation by cI does not change the rank of A, i.e., rank(A) = rank(cA).
1
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Solutions to Homework 7.

Math 110, Fall 2006.

Prob 3.1.3. To find the inverses of the elementary matrices, we must simply undo the corresponding elementary operations:

(a)

 (^) , (b)

 (^) , (c)

Prob 3.1.5. If E is an elementary matrix of type I corresponding to the swap or rows i and J, then E has 1 in positions (i, j) and (j, i), zeros in positions (i, i) and (j, j), and the other entries exactly as in the identity matrix of the appropriate size. But then E is symmetric, i.e., its transpose is E itself. Likewise, if E is of type II, then its transpose is itself. If E is of type III and corresponds to adding row j multiplied by c to row i, then it looks like the identity matrix except for the entry c in position (i, j). Then its transpose has c in position (j, i), which corresponds to adding row i multiplied by c to row j. So, in all three cases E is an elementary matrix if and only if so is Et.

Prob 3.2.2. (a) 2, (b) 3, (c) 2, (d) 1, (e) 3, (f) 3, (g) 1.

Prob 3.2.6.

(a) T is invertible. Writing the matrix of T in the standard basis for P 2 (IR) and inverting it, we get

T −^1 (ax^2 + bx + c) = −ax^2 − (4a + b)x − (10a + 2b + c).

(b) T is not invertible, since it has a nontrivial kernel, for example, T 1 = 0.

(c) T is invertible: the same approach as in (a) yields

T −^1 (a, b, c) =

a −

b +

c,

a −

c, −

a +

b +

c

(d) Representing T with respect to the standard bases for IR^3 and P 2 (IR) and inverting the obtained matrix, we get T −^1 (a + bx + cx^2 ) = (c, (a − b)/ 2 , (a + b − 2 c)/2).

(e) T is invertible, and T −^1 (a, b, c) =

a − b +

c

x^2 +

a +

c

x + b.

(f) T is not invertible: for example, the matrix

A =

[

]

is in the kernel of T , since both tr(A) and tr(EA) are zero, and the other two traces are also zero since tr(At) = tr(A) and tr(EA) = tr(AE) always.

Prob 3.2.8. Since cA = (cI)A and since the matrix cI is invertible for c 6 = 0, we conclude that multipli- cation by cI does not change the rank of A, i.e., rank(A) = rank(cA).

Prob 3.2.18. Let A 1 ,.. ., An be the columns of A and let B 1 ,.. ., Bn be the rows of B. Then

AB =

[

A 1 · · · An

]

B 1

Bn

 =^ A 1 B 1 +^ · · ·^ +^ AnBn.

Each matrix Aj Bj is a product of a column-vector and a row-vector, hence has rank at most 1. So, AB is a sum of n matrices each of which has rank at most 1.

Prob 3.3.1. (a) False, an inhomogeneous system may not have any solutions. (b) False, it may have multiple solutions. (c) True, the zero vector is always a solution. (d) False if the matrix of the system is not invertible. (e) False for inhomogeneous systems (as above). (f) False; the homogeneous system always has a solution but the inhomogeneous system may not. (g) True, the solution (zero) is then unique. (h) False for inhomogeneous system: it is a shifted subspace.

Prob 3.3.11. The farmer, tailor, and carpenter must have incomes in the proportions 4 : 3 : 4 since the vector [434]t^ is the eigenvector of A corresponding to its eigenvalue 1.

Prob 3.4.1. (a) False since operations on columns do not preserve the solutions. (b) True, row operations preserve the solutions. (c) True (proved in class). (d) True (proved in class). (e) False, it may or not be consistent depending on the vector in the right-hand side. (f) True (follows from properties of row echelon form). (g) True (like in (f)).

Prob 3.4.2.

(a) x 1 = 4, x 2 = −3, x 3 = −1. The reduced row echelon form of the augmented matrix is  

(b) x 1 = − 5 x 3 + 9, x 2 = − 3 x 3 + 4, where x 3 ∈ IR is free. The reduced row echelon form of the augmented matrix is (^) 

  

(c) x 1 = 2, x 2 = 3, x 3 = −2, x 4 = −1. The reduced row echelon form of the augmented matrix is    

(d) x 1 = 7/13, x 2 = 16/13, x 3 = 14/13, x 4 = − 18 /13. The reduced row echelon form of the augmented matrix is (^) 

  