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[PDF]MatrixAnalysis
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更新于2023-07-19
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这是一本英文的矩阵分析的书,书中内容详略得当,论述清晰,是极品中的极品,强烈推荐!!
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Contents
Preface
.......................ix
1. Linear Equations ..............1
1.1 Introduction . . . ............... 1
1.2 Gaussian Elimination and Matrices ........ 3
1.3 Gauss–Jordan Method ..............15
1.4 Two-Point Boundary Value Problems .......18
1.5 Making Gaussian Elimination Work ........21
1.6 Ill-Conditioned Systems .............33
2. Rectangular Systems and Echelon Forms . . . 41
2.1 Row Echelon Form and Rank ...........41
2.2 Reduced Row Echelon Form ...........47
2.3 Consistency of Linear Systems ..........53
2.4 Homogeneous Systems ..............57
2.5 Nonhomogeneous Systems ............64
2.6 Electrical Circuits . ...............73
3. Matrix Algebra .............. 79
3.1 From Ancient China to Arthur Cayley .......79
3.2 Addition and Transposition ...........81
3.3 Linearity ....................89
3.4 Why Do It This Way ..............93
3.5 Matrix Multiplication ..............95
3.6 Properties of Matrix Multiplication ....... 105
3.7 Matrix Inversion . .............. 115
3.8 Inverses of Sums and Sensitivity ........ 124
3.9 Elementary Matrices and Equivalence ...... 131
3.10 The LU Factorization ............. 141
4. Vector Spaces ...............159
4.1 Spaces and Subspaces ............. 159
4.2 Four Fundamental Subspaces .......... 169
4.3 Linear Independence ............. 181
4.4 Basis and Dimension ............. 194
vi Contents
4.5 More about Rank . .............. 210
4.6 Classical Least Squares ............ 223
4.7 Linear Transformations ............ 238
4.8 Change of Basis and Similarity ......... 251
4.9 Invariant Subspaces .............. 259
5. Norms, Inner Products, and Orthogonality . . 269
5.1 Vector Norms . . .............. 269
5.2 Matrix Norms . . .............. 279
5.3 Inner-Product Spaces ............. 286
5.4 Orthogonal Vectors .............. 294
5.5 Gram–Schmidt Procedure ........... 307
5.6 Unitary and Orthogonal Matrices ........ 320
5.7 Orthogonal Reduction ............. 341
5.8 Discrete Fourier Transform ........... 356
5.9 Complementary Subspaces ........... 383
5.10 Range-Nullspace Decomposition ........ 394
5.11 Orthogonal Decomposition ........... 403
5.12 Singular Value Decomposition ......... 411
5.13 Orthogonal Projection ............. 429
5.14 Why Least Squares? .............. 446
5.15 Angles between Subspaces ........... 450
6. Determinants ...............459
6.1 Determinants . . . .............. 459
6.2 Additional Properties of Determinants ...... 475
7. Eigenvalues and Eigenvectors ........489
7.1 Elementary Properties of Eigensystems ..... 489
7.2 Diagonalization by Similarity Transformations . . 505
7.3 Functions of Diagonalizable Matrices ...... 525
7.4 Systems of Differential Equations ........ 541
7.5 Normal Matrices . .............. 547
7.6 Positive Definite Matrices ........... 558
7.7 Nilpotent Matrices and Jordan Structure .... 574
7.8 Jordan Form . . . .............. 587
7.9 Functions of Nondiagonalizable Matrices ..... 599
Contents vii
7.10 Difference Equations, Limits, and Summability . . 616
7.11 Minimum Polynomials and Krylov Methods . . . 642
8. Perron–Frobenius Theory .........661
8.1 Introduction . . . .............. 661
8.2 Positive Matrices . .............. 663
8.3 Nonnegative Matrices ............. 670
8.4 Stochastic Matrices and Markov Chains ..... 687
Index
...................... 705
viii Contents
You are today where your knowledge brought you;
you will be tomorrow where your knowledge takes you.
— Anonymous
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