Problem Set 9 Unsolved Problems - Linear Algebra | MATH 3013, Assignments of Linear Algebra

Material Type: Assignment; Professor: Binegar; Class: LINEAR ALGEBRA; Subject: Mathematics ; University: Oklahoma State University - Stillwater; Term: Unknown 1989;

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Pre 2010

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Math 3013
Homework Set 9
Problems from §5.1 (pgs. 300-301 of text): 2,4,6,8,10,12,17,19,23
Problems from §5.2 (pgs. 315-317 of text): 1,2,3,4,5,9,10,13
Problems from §7.1 (pgs. 394-395 of text): 7,8,9,10
1. (Problems 5.1.2, 5.1.4, 5.1.6, 5.1.8, 5.1.10, and 5.1.12 in text). Find the characteristic polynomial, the
real eigenvalues, and the corresponding eigenvectors for the following matrices.
(a) A=7 5
10 8
(b) A=75
16 17
(c) A=12
1 2
(d) A=
1 0 0
4 2 1
403
(e) A=
100
8 4 5
809
(f) A=
4 0 0
7 2 1
703
2. (Problems 5.1.17 and 5.1.19 in text) Find the eigenvalues λiand the corresponding eigenvectors vifor
the following linear transformations.
(a) T([x, y]) = [2x3y, 3x+ 2y]
(b) T([x1, x2, x3]) = [x1+x3, x2, x1+x3]
3. Mark each of the following statements True or False.
(a) Every square matrix has real eigenvalues.
(b) Every n×nmatrix has ndistinct (possible complex) eigenvalues.
(c) Every n×nmatrix has nnot necessarily distinct and possibly complex eigenvalues.
(d) There can be only one eigenvalue associated with an eigenvector of a linear transformation.
(e) There can be only one eigenvector associated with an eigenvalue of a linear transformation.
(f) If vis an eigenvector of a matrix A, then vis an eigenvector of A+cIfor all scalars c.
(g) If λis an eigenvalue of a matrix A, then λis an eigenvalue of A+cIfor all scalars c.
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Math 3013

Homework Set 9

Problems from §5.1 (pgs. 300-301 of text): 2,4,6,8,10,12,17,19, Problems from §5.2 (pgs. 315-317 of text): 1,2,3,4,5,9,10, Problems from §7.1 (pgs. 394-395 of text): 7,8,9,

  1. (Problems 5.1.2, 5.1.4, 5.1.6, 5.1.8, 5.1.10, and 5.1.12 in text). Find the characteristic polynomial, the real eigenvalues, and the corresponding eigenvectors for the following matrices.

(a) A =

[

]

(b) A =

[

]

(c) A =

[

]

(d) A =

(e) A =

(f) A =

  1. (Problems 5.1.17 and 5.1.19 in text) Find the eigenvalues λi and the corresponding eigenvectors vi for the following linear transformations.

(a) T ([x, y]) = [2x − 3 y, − 3 x + 2y]

(b) T ([x 1 , x 2 , x 3 ]) = [x 1 + x 3 , x 2 , x 1 + x 3 ]

  1. Mark each of the following statements True or False.

(a) Every square matrix has real eigenvalues.

(b) Every n × n matrix has n distinct (possible complex) eigenvalues.

(c) Every n × n matrix has n not necessarily distinct and possibly complex eigenvalues.

(d) There can be only one eigenvalue associated with an eigenvector of a linear transformation.

(e) There can be only one eigenvector associated with an eigenvalue of a linear transformation.

(f) If v is an eigenvector of a matrix A, then v is an eigenvector of A + cI for all scalars c.

(g) If λ is an eigenvalue of a matrix A, then λ is an eigenvalue of A + cI for all scalars c. 1

2

(h) If v is an eigenvector of an invertible matrix A, then cv is an eigenvector of A−^1 for all non-zero scalars c.

(i) Every vector in a vector space V is an eigenvector of the identity transformation of V into V.

(j) Ever nonzero vector in a vector space V is an eigenvector of the identity transformation of V into V.

  1. (Problems 5.2.1, 5.2.2, 5.2.3, 5.2.4, 5.2.5 in text) Find the eigenvalues λi, the corresponding eigenvectors vi of the following matrices. Also find an invertible matrix C and a diagonal matrix D such that D = C−^1 AC.

(a) A =

[

]

(b) A =

[

]

(c) A =

[

]

(d) A =

(e) A =

  1. (Problems 5.2.9 and 5.2.10 in text) Determine whether or not the following matrices are diagonalizable.

(a) A =

(b) A =

  1. (Problem 5.2.13 in text) Mark each of the following True or False.

(a) Every n × n matrix is diagonalizable.

(b) If an n × n matrix has n distinct real eigenvalues, then it is diagonalizable.

(c) Every n × n real symmetric matrix is real diagonalizable.

(d) An n × n matrix is diagonalizable if and only if it has n real eigenvalues.

(e) An n × n matrix is diagonalizable if and only if the algebraic multiplicity of each of its eigenvalues equals the geometric multiplicity.

(f) Every invertible matrix is diagonalizable.

(g) Every triagular matrix is diagonalizable.