Linear Algebra, Theory And Applications, 2012a

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52 MATRICES AND LINEAR TRANSFORMATIONS 11. Use the result of Problem 10 to verify directly that (AB) T = B T A T without making any reference to subscripts. 12. Let x =(−1, −1, 1) and y =(0, 1, 2) . Find x T y and xy T if possible. 13. Give an example of matrices, A, B, C such that B ≠ C, A ≠0, and yet AB = AC. ⎛ 14. Let A = ⎝ 1 1 ⎞ ⎛ ( ) 1 −1 −2 −2 −1 ⎠, B = , and C = ⎝ 1 1 −3 ⎞ −1 2 0 ⎠ . Find 2 1 −2 1 2 −3 −1 0 if possible the following products. AB, BA, AC, CA, CB, BC. 15. Consider the following digraph. 1 2 3 4 Write the matrix associated with this digraph and find the number of ways to go from 3 to 4 in three steps. 16. Show that if A −1 exists for an n × n matrix, then it is unique. That is, if BA = I and AB = I, then B = A −1 . 17. Show (AB) −1 = B −1 A −1 . 18. Show that if A is an invertible n × n matrix, then so is A T and ( A T ) −1 = ( A −1 ) T . 19. Show that if A is an n × n invertible matrix and x is a n × 1 matrix such that Ax = b for b an n × 1 matrix, then x = A −1 b. 20. Give an example of a matrix A such that A 2 = I and yet A ≠ I and A ≠ −I. 21. Give an example of matrices, A, B such that neither A nor B equals zero and yet AB =0. ⎛ ⎞ ⎛ ⎞ x 1 − x 2 +2x 3 x 1 22. Write ⎜ 2x 3 + x 1 ⎟ ⎝ 3x 3 ⎠ in the form A ⎜ x 2 ⎟ ⎝ x 3 ⎠ where A is an appropriate matrix. 3x 4 +3x 2 + x 1 x 4 23. Give another example other than the one given in this section of two square matrices, A and B such that AB ≠ BA. 24. Suppose A and B are square matrices of the same size. Which of the following are correct? (a) (A − B) 2 = A 2 − 2AB + B 2 (b) (AB) 2 = A 2 B 2 (c) (A + B) 2 = A 2 +2AB + B 2 (d) (A + B) 2 = A 2 + AB + BA + B 2
2.3. LINEAR TRANSFORMATIONS 53 (e) A 2 B 2 = A (AB) B (f) (A + B) 3 = A 3 +3A 2 B +3AB 2 + B 3 (g) (A + B)(A − B) =A 2 − B 2 (h) None of the above. They are all wrong. (i) All of the above. They are all right. ( ) −1 −1 25. Let A = . Find all 2 × 2 matrices, B such that AB =0. 3 3 26. Prove that if A −1 exists and Ax = 0 then x = 0. 27. Let 28. Let 29. Let 30. Let ⎛ A = ⎝ 1 2 3 ⎞ 2 1 4 ⎠ . 1 0 2 Find A −1 if possible. If A −1 does not exist, determine why. ⎛ A = ⎝ 1 0 3 ⎞ 2 3 4 ⎠ . 1 0 2 Find A −1 if possible. If A −1 does not exist, determine why. ⎛ A = ⎝ 1 2 3 2 1 4 4 5 10 ⎞ ⎠ . Find A −1 if possible. If A −1 does not exist, determine why. A = ⎛ ⎜ ⎝ 1 2 0 2 1 1 2 0 2 1 −3 2 1 2 1 2 Find A −1 if possible. If A −1 does not exist, determine why. 2.3 <strong>Linear</strong> Transformations By (2.13), if A is an m × n matrix, then for v, u vectors in F n and a, b scalars, ⎞ ⎟ ⎠ ⎛ ⎞ ∈F { }} n { A ⎝au + bv⎠ = aAu + bAv ∈ F m (2.19) Definition 2.3.1 A function, A : F n → F m is called a linear transformation if for all u, v ∈ F n and a, b scalars, (2.19) holds. From (2.19), matrix multiplication defines a linear transformation as just defined. It turns out this is the only type of linear transformation available. Thus if A is a linear transformation from F n to F m , there is always a matrix which produces A. Before showing this, here is a simple definition.
Page 1 and 2: Linear Algebra, Theory And Applicat
Page 3 and 4: Contents 1 Preliminaries 11 1.1 Set
Page 5 and 6: CONTENTS 5 8 Vector Spaces And Fiel
Page 7 and 8: CONTENTS 7 E The Fundamental Theore
Page 9 and 10: Preface This is a book on linear al
Page 11 and 12: Preliminaries 1.1 Sets And Set Nota
Page 13 and 14: 1.3. THE NUMBER LINE AND ALGEBRA OF
Page 15 and 16: 1.5. THE COMPLEX NUMBERS 15 Also fr
Page 17 and 18: 1.5. THE COMPLEX NUMBERS 17 and so
Page 19 and 20: 1.6. EXERCISES 19 Eventually, for r
Page 21 and 22: 1.8. WELL ORDERING AND ARCHIMEDEAN
Page 23 and 24: 1.9. DIVISION AND NUMBERS 23 Theore
Page 25 and 26: 1.9. DIVISION AND NUMBERS 25 Exampl
Page 27 and 28: 1.10. SYSTEMS OF EQUATIONS 27 Why i
Page 29 and 30: 1.10. SYSTEMS OF EQUATIONS 29 The a
Page 31 and 32: 1.11. EXERCISES 31 It follows x =
Page 33 and 34: 1.14. EXERCISES 33 the existence of
Page 35 and 36: 1.15. THE INNER PRODUCT IN F N 35 s
Page 37 and 38: Matrices And Linear Transformations
Page 39 and 40: 2.1. MATRICES 39 Definition 2.1.2 M
Page 41 and 42: 2.1. MATRICES 41 is it possible to
Page 43 and 44: 2.1. MATRICES 43 a3× 3 matrix as d
Page 45 and 46: 2.1. MATRICES 45 1 2 3 4 Write the
Page 47 and 48: = ∑ k ( B T ) ik ( A T ) kj 2.1.
Page 49 and 50: 2.1. MATRICES 49 As described above
Page 51: 2.2. EXERCISES 51 Write the augment
Page 55 and 56: 2.3. LINEAR TRANSFORMATIONS 55 Proo
Page 57 and 58: 2.4. SUBSPACES AND SPANS 57 Proof:
Page 59 and 60: 2.4. SUBSPACES AND SPANS 59 Proof 3
Page 61 and 62: 2.5. AN APPLICATION TO MATRICES 61
Page 63 and 64: 2.6. MATRICES AND CALCULUS 63 2.6.1
Page 65 and 66: 2.6. MATRICES AND CALCULUS 65 where
Page 67 and 68: 2.6. MATRICES AND CALCULUS 67 There
Page 69 and 70: 2.6. MATRICES AND CALCULUS 69 Using
Page 71 and 72: 2.7. EXERCISES 71 this will suffice
Page 73 and 74: 2.7. EXERCISES 73 22. If A is a lin
Page 75 and 76: 2.7. EXERCISES 75 35. ↑Suppose yo
Page 77 and 78: Determinants 3.1 Basic Techniques A
Page 79 and 80: 3.1. BASIC TECHNIQUES AND PROPERTIE
Page 81 and 82: 3.2. EXERCISES 81 First note det (A
Page 83 and 84: 3.3. THE MATHEMATICAL THEORY OF DET
Page 97 and 98: 3.4. THE CAYLEY HAMILTON THEOREM 97
Page 99 and 100: 3.5. BLOCK MULTIPLICATION OF MATRIC
Page 101 and 102: 3.5. BLOCK MULTIPLICATION OF MATRIC
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3.6. EXERCISES 103 derivatives so i
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Row Operations 4.1 Elementary Matri
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4.1. ELEMENTARY MATRICES 107 This h
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4.1. ELEMENTARY MATRICES 109 Now co
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4.2. THE RANK OF A MATRIX 111 So ho
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4.3. THE ROW REDUCED ECHELON FORM 1
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4.3. THE ROW REDUCED ECHELON FORM 1
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4.5. FREDHOLM ALTERNATIVE 117 Proof
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4.6. EXERCISES 119 5. ↑Consider t
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4.6. EXERCISES 121 18. Suppose A is
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Some Factorizations 5.1 LU Factoriz
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5.3. SOLVING LINEAR SYSTEMS USING A
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5.5. JUSTIFICATION FOR THE MULTIPLI
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5.6. EXISTENCE FOR THE PLU FACTORIZ
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5.7. THE QR FACTORIZATION 131 so it
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5.8. EXERCISES 133 Theorem 5.7.5 Le
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Linear Programming 6.1 Simple Geome
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6.2. THE SIMPLEX TABLEAU 137 set x
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6.2. THE SIMPLEX TABLEAU 139 lution
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6.3. THE SIMPLEX ALGORITHM 141 Let
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6.3. THE SIMPLEX ALGORITHM 143 the
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6.3. THE SIMPLEX ALGORITHM 145 by 2
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6.3. THE SIMPLEX ALGORITHM 147 I ne
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6.3. THE SIMPLEX ALGORITHM 149 Of c
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6.4. FINDING A BASIC FEASIBLE SOLUT
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6.5. DUALITY 153 Now recall that to
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6.5. DUALITY 155 and there are stil
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Spectral Theory Spectral Theory ref
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7.1. EIGENVALUES AND EIGENVECTORS O
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7.2. SOME APPLICATIONS OF EIGENVALU
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7.3. EXERCISES 167 Therefore, the e
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7.3. EXERCISES 169 22. Find the com
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7.3. EXERCISES 171 38. Let M be an
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7.4. SCHUR’S THEOREM 173 7.4 Schu
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7.4. SCHUR’S THEOREM 175 Proof: L
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7.4. SCHUR’S THEOREM 177 and furt
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7.4. SCHUR’S THEOREM 179 Proof: F
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7.6. QUADRATIC FORMS 181 7.6 Quadra
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7.7. SECOND DERIVATIVE TEST 183 Cor
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7.7. SECOND DERIVATIVE TEST 185 The
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7.9. ADVANCED THEOREMS 187 for find
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7.9. ADVANCED THEOREMS 189 Proof: D
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7.10. EXERCISES 191 Show that the a
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7.10. EXERCISES 193 27. Let f (x, y
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7.10. EXERCISES 195 40. In the abov
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7.10. EXERCISES 197 44. Show that i
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Vector Spaces And Fields 8.1 Vector
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8.2. SUBSPACES AND BASES 201 8.2.2
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8.2. SUBSPACES AND BASES 203 Defini
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8.3. LOTS OF FIELDS 205 such that 0
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8.3. LOTS OF FIELDS 207 and this is
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8.3. LOTS OF FIELDS 209 Lemma 8.3.9
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8.3. LOTS OF FIELDS 211 Definition
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8.3. LOTS OF FIELDS 213 Then, since
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8.3. LOTS OF FIELDS 215 Proposition
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8.3. LOTS OF FIELDS 217 where deg r
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8.4. EXERCISES 219 8.3.4 The Lindem
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8.4. EXERCISES 221 18. If you have
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8.4. EXERCISES 223 first is not har
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Linear Transformations 9.1 Matrix M
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9.3. THE MATRIX OF A LINEAR TRANSFO
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9.5. EXERCISES 243 9. ↑In the sit
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Linear Transformations Canonical Fo
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10.1. A THEOREM OF SYLVESTER, DIREC
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10.2. DIRECT SUMS, BLOCK DIAGONAL M
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10.3. CYCLIC SETS 251 while ⎛ ⎞
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10.3. CYCLIC SETS 253 Since β x is
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10.4. NILPOTENT TRANSFORMATIONS 255
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10.5. THE JORDAN CANONICAL FORM 257
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10.6. EXERCISES 263 8. Let ⎛ A =
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10.6. EXERCISES 265 Now use this in
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10.7. THE RATIONAL CANONICAL FORM 2
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10.8. UNIQUENESS 269 Thus the matri
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10.8. UNIQUENESS 271 The characteri
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10.9. EXERCISES 273 Then doing the
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Markov Chains And Migration Process
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11.1. REGULAR MARKOV MATRICES 277 O
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11.2. MIGRATION MATRICES 279 11.2 M
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11.3. MARKOV CHAINS 281 After many
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11.3. MARKOV CHAINS 283 and the fac
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11.4. EXERCISES 285 5. Show that wh
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Inner Product Spaces 12.1 General T
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12.2. THE GRAM SCHMIDT PROCESS 289
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12.2. THE GRAM SCHMIDT PROCESS 291
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12.3. RIESZ REPRESENTATION THEOREM
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12.4. THE TENSOR PRODUCT OF TWO VEC
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12.5. LEAST SQUARES 297 Lemma 12.5.
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12.7. EXERCISES 299 4. Let ||x||
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12.7. EXERCISES 301 (√ √ ) 2 C
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12.8. THE DETERMINANT AND VOLUME 30
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12.8. THE DETERMINANT AND VOLUME 30
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Self Adjoint Operators 13.1 Simulta
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13.1. SIMULTANEOUS DIAGONALIZATION
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13.2. SCHUR’S THEOREM 311 Proof:
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13.3. SPECTRAL THEORY OF SELF ADJOI
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13.3. SPECTRAL THEORY OF SELF ADJOI
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13.4. POSITIVE AND NEGATIVE LINEAR
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13.5. FRACTIONAL POWERS 319 Proof:
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13.5. FRACTIONAL POWERS 321 Proof:
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13.6. POLAR DECOMPOSITIONS 323 Proo
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13.7. AN APPLICATION TO STATISTICS
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13.8. THE SINGULAR VALUE DECOMPOSIT
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13.9. APPROXIMATION IN THE FROBENIU
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13.10. LEAST SQUARES AND SINGULAR V
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13.11. THE MOORE PENROSE INVERSE 33
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13.12. EXERCISES 335 8. Prove the C
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Norms For Finite Dimensional Vector
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339 This proves the first half of t
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341 Next consider the claim that ||
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14.1. THE P NORMS 343 14.1 The p No
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14.2. THE CONDITION NUMBER 345 Thus
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14.2. THE CONDITION NUMBER 347 Sinc
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14.3. THE SPECTRAL RADIUS 349 ⎛ =
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14.4. SERIES AND SEQUENCES OF LINEA
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14.4. SERIES AND SEQUENCES OF LINEA
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14.5. ITERATIVE METHODS FOR LINEAR
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14.6. THEORY OF CONVERGENCE 361 Lem
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14.7. EXERCISES 363 Proof: From Lem
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14.7. EXERCISES 365 11. Suppose ρ
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14.7. EXERCISES 367 Next take e tλ
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14.7. EXERCISES 369 24. Suppose A i
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Numerical Methods For Finding Eigen
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15.1. THE POWER METHOD FOR EIGENVAL
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15.2. THE QR ALGORITHM 387 each a v
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15.2. THE QR ALGORITHM 389 Proof: L
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15.2. THE QR ALGORITHM 391 where
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15.2. THE QR ALGORITHM 393 Corollar
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15.2. THE QR ALGORITHM 395 below th
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15.2. THE QR ALGORITHM 397 where R
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15.2. THE QR ALGORITHM 399 A matrix
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15.3. EXERCISES 401 where A k = Q k
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Positive Matrices Earlier theorems
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405 |μ| ≤λ 0 . But also, the fa
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407 which says x 0 −x 0 v T x 0 =
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409 must have the same argument for
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Functions Of Matrices The existence
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413 There is no convergence problem
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415 This gives us a nice definition
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Applications To Differential Equati
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C.3. LOCAL SOLUTIONS 419 C.3 Local
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C.4. FIRST ORDER LINEAR SYSTEMS 421
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C.5. GEOMETRIC THEORY OF AUTONOMOUS
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C.5. GEOMETRIC THEORY OF AUTONOMOUS
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C.6. GENERAL GEOMETRIC THEORY 433 T
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C.7. THESTABLEMANIFOLD 435 Lemma C.
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C.7. THESTABLEMANIFOLD 437 ≤ e γ
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Compactness And Completeness D.0.1
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441 |a k − a l | < ε 2 .Thenifk>
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The Fundamental Theorem Of Algebra
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Fields And Field Extensions F.1 The
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F.2. THE FUNDAMENTAL THEOREM OF ALG
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F.2. THE FUNDAMENTAL THEOREM OF ALG
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F.3. TRANSCENDENTAL NUMBERS 451 F.3
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F.3. TRANSCENDENTAL NUMBERS 453 It
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F.3. TRANSCENDENTAL NUMBERS 455 Not
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F.3. TRANSCENDENTAL NUMBERS 457 Thi
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F.4. MORE ON ALGEBRAIC FIELD EXTENS
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F.5. THE GALOIS GROUP 465 a rationa
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F.5. THE GALOIS GROUP 467 Now let
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F.6. NORMAL SUBGROUPS 469 If H is a
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F.8. CONDITIONS FOR SEPARABILITY 47
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F.8. CONDITIONS FOR SEPARABILITY 47
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F.9. PERMUTATIONS 475 of f (x) ands
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F.9. PERMUTATIONS 477 smallest k
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F.10. SOLVABLE GROUPS 479 Then i 1
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F.10. SOLVABLE GROUPS 481 Thus ever
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F.11. SOLVABILITY BY RADICALS 483 A
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Bibliography [1] Apostol T., Calcul
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Answers To Selected Exercises G.1 E
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G.7. EXERCISES 489 15 Find the matr
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G.10. EXERCISES 491 11 It follows f
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G.13. EXERCISES 493 19 ⎛ ⎝ 4
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G.19. EXERCISES 495 8 λ 3 − λ 2
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G.23. EXERCISES 497 ⎧⎛ ⎞⎫
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INDEX 499 defective, 162 DeMoivre i
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INDEX 501 rotation, 235 linear tran
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INDEX 503 scalars, 18, 32, 37 Schur
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