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线性代数和矩阵理论是数学和自然科学的基本工具,同时也是科学研究的沃土。本书是矩阵理论方面的经典著作,从数学分析的角度阐述了矩阵分析的经典和现代方法。主要内容有:特征值、特征向量和相似性;酉相似和酉等价;相似标准型和三角分解;Hermite矩阵、对称矩阵和酉相合;向量范数和矩阵范数;特征值的估计和扰动;正定矩阵和半正定矩阵;正矩阵和非负矩阵。
第2版对第1版进行了全面的修订、更新和扩展。这一版不仅对基础线性代数和矩阵理论做了全面的总结,而且还新增了奇异值、CS分解和Weyr标准型的相关内容,扩展了与逆矩阵和分块矩阵相关的内容,介绍了Jordan标准型的新应用。此外,还附有1100多个问题和练习,并且给出了一些提示,以帮助读者提高解决数学问题的能力。
本书可以用作本科生或者研究生的教材,也可用作数学工作者和科技人员的参考书。
内容简介
矩阵理论作为一种基本的数学工具,在数学与其他科学技术领域都有广泛应用。本书从数学分析的角度阐述了矩阵分析的经典和现代方法。主要内容有:特征值、特征向量和相似性;酉相似和酉等价;相似标准型和三角分解;Hermite矩阵、对称矩阵和酉相合;向量范数和矩阵范数;特征值的估计和扰动;正定矩阵和半正定矩阵;正矩阵和非负矩阵。第2版进行了全面的修订和更新,用新的小节介绍了奇异值、CS分解和Weyr范式等其他内容,并附有1100多个线性代数课程的问题和练习。
作者简介
Roger A. Horn
国际知名数学专家,现任美国犹他大学数学系研究教授,曾任约翰?霍普金斯大学数学系系主任,并曾任American Mathematical Monthly编辑。
Charles R. Johnson
国际知名数学专家,现任美国威廉玛丽学院教授。因其在数学科学领域的杰出贡献被授予华盛顿科学学会奖。
目录
Preface to the Second Edition page ix
Preface to the First Edition xiii
0 Review and Miscellanea 1
0.0 Introduction 1
0.1 Vector spaces 1
0.2 Matrices 5
0.3 Determinants 8
0.4 Rank 12
0.5 Nonsingularity 14
0.6 The Euclidean inner product and norm 15
0.7 Partitioned sets and matrices 16
0.8 Determinants again 21
0.9 Special types of matrices 30
0.10 Change of basis 39
0.11 Equivalence relations 40
1 Eigenvalues, Eigenvectors, and Similarity 43
1.0 Introduction 43
1.1 The eigenvalue–eigenvector equation 44
1.2 The characteristic polynomial and algebraic multiplicity 49
1.3 Similarity 57
1.4 Left and right eigenvectors and geometric multiplicity 75
2 Unitary Similarity and Unitary Equivalence 83
2.0 Introduction 83
2.1 Unitary matrices and the QR factorization 83
2.2 Unitary similarity 94
2.3 Unitary and real orthogonal triangularizations 101
2.4 Consequences of Schur’s triangularization theorem 108
2.5 Normal matrices 131
2.6 Unitary equivalence and the singular value decomposition 149
2.7 The CS decomposition 159
3 Canonical Forms for Similarity and Triangular Factorizations 163
3.0 Introduction 163
3.1 The Jordan canonical form theorem 164
3.2 Consequences of the Jordan canonical form 175
3.3 The minimal polynomial and the companion matrix 191
3.4 The real Jordan and Weyr canonical forms 201
3.5 Triangular factorizations and canonical forms 216
4 Hermitian Matrices, Symmetric Matrices, and Congruences 225
4.0 Introduction 225
4.1 Properties and characterizations of Hermitian matrices 227
4.2 Variational characterizations and subspace intersections 234
4.3 Eigenvalue inequalities for Hermitian matrices 239
4.4 Unitary congruence and complex symmetric matrices 260
4.5 Congruences and diagonalizations 279
4.6 Consimilarity and condiagonalization 300
5 Norms for Vectors and Matrices 313
5.0 Introduction 313
5.1 Definitions of norms and inner products 314
5.2 Examples of norms and inner products 320
5.3 Algebraic properties of norms 324
5.4 Analytic properties of norms 324
5.5 Duality and geometric properties of norms 335
5.6 Matrix norms 340
5.7 Vector norms on matrices 371
5.8 Condition numbers: inverses and linear systems 381
6 Location and Perturbation of Eigenvalues 387
6.0 Introduction 387
6.1 Gerˇsgorin discs 387
6.2 Gerˇsgorin discs – a closer look 396
6.3 Eigenvalue perturbation theorems 405
6.4 Other eigenvalue inclusion sets 413
7 Positive Definite and Semidefinite Matrices 425
7.0 Introduction 425
7.1 Definitions and properties 429
7.2 Characterizations and properties 438
7.3 The polar and singular value decompositions 448
7.4 Consequences of the polar and singular value decompositions 458
7.5 The Schur product theorem 477
7.6 Simultaneous diagonalizations, products, and convexity 485
7.7 The Loewner partial order and block matrices 493
7.8 Inequalities involving positive definite matrices 505
8 Positive and Nonnegative Matrices 517
8.0 Introduction 517
8.1 Inequalities and generalities 519
8.2 Positive matrices 524
8.3 Nonnegative matrices 529
8.4 Irreducible nonnegative matrices 533
8.5 Primitive matrices 540
8.6 A general limit theorem 545
8.7 Stochastic and doubly stochastic matrices 547
Appendix A Complex Numbers 555
Appendix B Convex Sets and Functions 557
Appendix C The Fundamental Theorem of Algebra 561
Appendix D Continuity of Polynomial Zeroes and Matrix
Eigenvalues 563
Appendix E Continuity, Compactness, and Weierstrass’s Theorem 565
Appendix F Canonical Pairs 567
References 571
Notation 575
Hints for Problems 579
Index 607
精彩书摘
《矩阵分析 英文版 第2版》:
Exercise.Explain why every diagonal matrix is normal.If a diagonal matrix is Hermitian,why must it be real?
Exercise.Show that each of the classes of unitary,Hermitian,and skew—Hermitian matrices is closed under unitary similarity.If A is unitary and |α|= 1,show that a A is unitary.If A is Hermitian and a is real,show that α A is Hermitian.If A is skew Hermitian and a is real,show that αA is skew Hermitian.
Exercise.Show that a Hermitian matrix has real main diagonal entries.Show that a skew—Hermitian matrix has pure imaginary main diagonal entries.What are the main diagonal entries of a real skew—symmetric matrix?
Exercise.Review the proof of(1.3.7)and conclude that A ∈ Mn is unitarily diagonalizable if and only if there is a set of n orthonormal vectors in Cn,each of which is an eigenvector of A.
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前言/序言
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