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E-grāmata: Matrix Theory: From Generalized Inverses to Jordan Form

(Baylor University, Texas, USA), (Baylor University, Texas, USA)
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In 1990, the National Science Foundation recommended that every college mathematics curriculum should include a second course in linear algebra. In answer to this recommendation, Matrix Theory: From Generalized Inverses to Jordan Form provides the material for a second semester of linear algebra that probes introductory linear algebra concepts while also exploring topics not typically covered in a sophomore-level class.

Tailoring the material to advanced undergraduate and beginning graduate students, the authors offer instructors flexibility in choosing topics from the book. The text first focuses on the central problem of linear algebra: solving systems of linear equations. It then discusses LU factorization, derives Sylvester's rank formula, introduces full-rank factorization, and describes generalized inverses. After discussions on norms, QR factorization, and orthogonality, the authors prove the important spectral theorem. They also highlight the primary decomposition theorem, Schur's triangularization theorem, singular value decomposition, and the Jordan canonical form theorem. The book concludes with a chapter on multilinear algebra.

With this classroom-tested text students can delve into elementary linear algebra ideas at a deeper level and prepare for further study in matrix theory and abstract algebra.

Recenzijas

Each chapter ends with a list of references for further reading. Undoubtedly, these will be useful for anyone who wishes to pursue the topics deeper. the book has many MATLAB examples and problems presented at appropriate places. the book will become a widely used classroom text for a second course on linear algebra. It can be used profitably by graduate and advanced level undergraduate students. It can also serve as an intermediate course for more advanced texts in matrix theory. This is a lucidly written book by two authors who have made many contributions to linear and multilinear algebra. K.C. Sivakumar, IMAGE, No. 47, Fall 2011

Always mathematically constructive, this book helps readers delve into elementary linear algebra ideas at a deeper level and prepare for further study in matrix theory and abstract algebra. Lenseignement Mathématique, January-June 2007, Vol. 53, No. 1-2

1 The Idea of Inverse
1
1.1 Solving Systems of Linear Equations
1
1.1.1 Numerical Note
10
1.1.1.1 Floating Point Arithmetic
10
1.1.1.2 Arithmetic Operations
11
1.1.1.3 Loss of Significance
12
1.1.2 MATLAB Moment
13
1.1.2.1 Creating Matrices in MATLAB
13
1.2 The Special Case of "Square" Systems
17
1.2.1 The Henderson Searle Formulas
21
1.2.2 Schur Complements and the Sherman-Morrison-Woodbury Formula
24
1.2.3 MATLAB Moment
37
1.2.3.1 Computing Inverse Matrices
37
1.2.4 Numerical Note
39
1.2.4.1 Matrix Inversion
39
1.2.4.2 Operation Counts
39
2 Generating Invertible Matrices
41
2.1 A Brief Review of Gauss Elimination with Back Substitution
41
2.1.1 MATLAB Moment
47
2.1.1.1 Solving Systems of Linear Equations
47
2.2 Elementary Matrices
49
2.2.1 The Minimal Polynomial
57
2.3 The LU and LDU Factorization
63
2.3.1 MATLAB Moment
75
2.3.1.1 The LU Factorization
75
2.4 The Adjugate of a Matrix
76
2.5 The Frame Algorithm and the Cayley-Hamilton Theorem
81
2.5.1 Digression on Newton's Identities
85
2.5.2 The Characteristic Polynomial and the Minimal Polynomial
90
2.5.3 Numerical Note
95
2.5.3.1 The Frame Algorithm
95
2.5.4 MATLAB Moment
95
2.5.4.1 Polynomials in MATLAB
95
3 Subspaces Associated to Matrices
99
3.1 Fundamental Subspaces
99
3.1.1 MATLAB Moment
109
3.1.1.1 The Fundamental Subspaces
109
3.2 A Deeper Look at Rank
111
3.3 Direct Sums and Idempotents
117
3.4 The Index of a Square Matrix
128
3.4.1 MATLAB Moment
147
3.4.1.1 The Standard Nilpotent Matrix
147
3.5 Left and Right Inverses
148
4 The Moore-Penrose Inverse
155
4.1 Row Reduced Echelon Form and Matrix Equivalence
155
4.1.1 Matrix Equivalence
160
4.1.2 MATLAB Moment
167
4.1.2.1 Row Reduced Echelon Form
167
4.1.3 Numerical Note
169
4.1.3.1 Pivoting Strategies
169
4.1.3.2 Operation Counts
170
4.2 The Hermite Echelon Form
171
4.3 Full Rank Factorization
176
4.3.1 MATLAB Moment
179
4.3.1.1 Full Rank Factorization
179
4.4 The Moore-Penrose Inverse
179
4.4.1 MATLAB Moment
190
4.4.1.1 The Moore-Penrose Inverse
190
4.5 Solving Systems of Linear Equations
190
4.6 Schur Complements Again (optional)
194
5 Generalized Inverses
199
5.1 The {1}-Inverse
199
5.2 {1,2}-Inverses
208
5.3 Constructing Other Generalized Inverses
210
5.4 {2}-Inverses
217
5.5 The Drazin Inverse
223
5.6 The Group Inverse
230
6 Norms
233
6.1 The Normed Linear Space Cn
233
6.2 Matrix Norms
244
6.2.1 MATLAB Moment
252
6.2.1.1 Norms
252
7 Inner Products
257
7.1 The Inner Product Space C"
257
7.2 Orthogonal Sets of Vectors in CI'
262
7.2.1 MATLAB Moment
269
7.2.1.1 The Gram-Schmidt Process
269
7.3 QR Factorization
269
7.3.1 Kung's Algorithm
274
7.3.2 MATLAB Moment
276
7.3.2.1 The QR Factorization
276
7.4 A Fundamental Theorem of Linear Algebra
278
7.5 Minimum Norm Solutions
282
7.6 Least Squares
285
8 Projections
291
8.1 Orthogonal Projections
291
8.2 The Geometry of Subspaces and the Algebra of Projections
299
8.3 The Fundamental Projections of a Matrix
309
8.3.1 MATLAB Moment
313
8.3.1.1 The Fundamental Projections
313
8.4 Full Rank Factorizations of Projections
313
8.5 Affine Projections
315
8.6 Quotient Spaces (optional)
324
9 Spectral Theory
329
9.1 Eigenstuff
329
9.1.1 MATLAB Moment
337
9.1.1.1 Eigenvalues and Eigenvectors in MATLAB
337
9.2 The Spectral Theorem
338
9.3 The Square Root and Polar Decomposition Theorems
347
10 Matrix Diagonalization 351
10.1 Diagonalization with Respect to Equivalence
351
10.2 Diagonalization with Respect to Similarity
357
10.3 Diagonalization with Respect to a Unitary
371
10.3.1 MATLAB Moment
376
10.3.1.1 Schur Triangularization
376
10.4 The Singular Value Decomposition
377
10.4.1 MATLAB Moment
385
10.4.1.1 The Singular Value Decomposition
385
11 Jordan Canonical Form 389
11.1 Jordan Form and Generalized Eigenvectors
389
11.1.1 Jordan Blocks
389
11.1.1.1 MATLAB Moment
392
11.1.2 Jordan Segments
392
11.1.2.1 MATLAB Moment
395
11.1.3 Jordan Matrices
396
11.1.3.1 MATLAB Moment
397
11.1.4 Jordan's Theorem
398
11.1.4.1 Generalized Eigenvectors
402
11.2 The Smith Normal Form (optional)
422
12 Multilinear Matters 431
12.1 Bilinear Forms
431
12.2 Matrices Associated to Bilinear Forms
437
12.3 Orthogonality
440
12.4 Symmetric Bilinear Forms
442
12.5 Congruence and Symmetric Matrices
447
12.6 Skew-Symmetric Bilinear Forms
450
12.7 Tensor Products of Matrices
452
12.7.1 MATLAB Moment
456
12.7.1.1 Tensor Product of Matrices
456
Appendix A Complex Numbers 459
A.1 What Is a Scalar?
459
A.2 The System of Complex Numbers
464
A.3 The Rules of Arithmetic in C
466
A.3.1 Basic Rules of Arithmetic in C
466
A.3.1.1 Associative Law of Addition
466
A.3.1.2 Existence of a Zero
466
A.3.1.3 Existence of Opposites
466
A.3.1.4 Commutative Law of Addition
466
A.3.1.5 Associative Law of Multiplication
467
A.3.1.6 Distributive Laws
467
A.3.1.7 Commutative Law for Multiplication
467
A.3.1.8 Existence of Identity
467
A.3.1.9 Existence of Inverses
467
A.4 Complex Conjugation, Modulus, and Distance
468
A.4.1 Basic Facts about Complex Conjugation
469
A.4.2 Basic Facts about Magnitude
469
A.4.3 Basic Properties of Distance
470
A.5 The Polar Form of Complex Numbers
473
A.6 Polynomials over C
480
A.7 Postscript
482
Appendix B Basic Matrix Operations 485
B.1 Introduction
485
B.2 Matrix Addition
487
B.3 Scalar Multiplication
489
B.4 Matrix Multiplication
490
B.5 Transpose
495
B.5.1 MATLAB Moment
502
B.5.1.1 Matrix Manipulations
502
B.6 Submatrices
503
B.6.1 MATLAB Moment
506
B.6.1.1 Getting at Pieces of Matrices
506
Appendix C Determinants 509
C.1 Motivation
509
C.2 Defining Determinants
512
C.3 Some Theorems about Determinants
517
C.3.1 Minors
517
C.3.2 The Cauchy-Binet Theorem
517
C.3.3 The Laplace Expansion Theorem
520
C.4 The Trace of a Square Matrix
528
Appendix D A Review of Basics 531
D.1 Spanning
531
D.2 Linear Independence
533
D.3 Basis and Dimension
534
D.4 Change of Basis
538
Index 543


Piziak, Robert; Odell, P.L.