矩阵分析
作 者:(美)霍恩(Roger A.Horn),(美)约翰逊(Charles R.Johnson) 著
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定 价:99
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出 版 社:人民邮电出版社
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出版日期:2015年11月01日
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页 数:643
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装 帧:平装
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ISBN:9787115405692
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![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。
霍恩、约翰逊编写的《矩阵分析(英文版第2版)》适合工程、统计、经济学、数学等专业的高年级本科生和研究生，以及数学工作者和科技人员阅读。
![作者简介]()
Roger A. Horn，靠前知名数学专家，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，靠前知名数学专家，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。
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Preface to the Second Edition page
Preface to the First Edition
0 Review and Miscellanea
0.0 Introduction
0.1 Vector spaces
0.2 Matrices
0.3 Determinants
0.4 Rank
0.5 Nonsingularity
0.6 The Euclidean inner product and norm
0.7 Partitioned sets and matrices
0.8 Determinants again
0.9 Special types of matrices
0.10 Change of basis
0.11 Equivalence relations
1 Eigenvalues, Eigenvectors, and Similarity
1.0 Introduction
1.1 The eigenvalue·eigenvector equation
1.2 The characteristic polynomial and algebraic multiplicity
1.3 Similarity
1.4 Left and right eigenvectors and geometric multiplicity
2 Unitary Similarity and Unitary Equivalence
2.0 Introduction
2.1 Unitary matrices and the QR factorization
2.2 Unitary similarity
2.3 Unitary and real orthogonal triangularizations
2.4 Consequences of Schur’s triangularization theorem
2.5 Normal matrices
2.6 Unitary equivalence and the singular value decomposition
2.7 The CS decomposition
3 Canonical Forms for Similarity and Triangular Factorizations
3.0 Introduction
3.1 The Jordan canonical form theorem
3.2 Consequences of the Jordan canonical form
3.3 The minimal polynomial and the companion matrix
3.4 The real Jordan and Weyr canonical forms
3.5 Triangular factorizations and canonical forms
4 Hermitian Matrices, Symmetric Matrices, and Congruences
4.0 Introduction
4.1 Properties and characterizations of Hermitian matrices
4.2 Variational characterizations and subspace intersections
4.3 Eigenvalue inequalities for Hermitian matrices
4.4 Unitary congruence and complex symmetric matrices
4.5 Congruences and diagonalizations
4.6 Consimilarity and condiagonalization
5 Norms for Vectors and Matrices
5.0 Introduction
5.1 Definitions of norms and inner products
5.2 Examples of norms and inner products
5.3 Algebraic properties of norms
5.4 Analytic properties of norms
5.5 Duality and geometric properties of norms
5.6 Matrix norms
5.7 Vector norms on matrices
5.8 Condition numbers: inverses and linear systems
6 Location and Perturbation of Eigenvalues
6.0 Introduction
6.1 Gergorin discs
6.2 Gergorin discs'a closer look
6.3 Eigenvalue perturbation theorems
6.4 Other eigenvalue inclusion sets
7 Positive Definite and Semidefinite Matrices
7.0 Introduction
7.1 Definitions and properties
7.2 Characterizations and properties
7.3 The polar and singular value decompositions
7.4 Consequences of the polar and singular value decompositions
7.5 The Schur product theorem
7.6 Simultaneous diagonalizations, products, and convexity
7.7 The Loewner partial order and block matrices
7.8 Inequalities involving positive definite matrices
8 Positive and Nonnegative Matrices
8.0 Introduction
8.1 Inequalities and generalities
8.2 Positive matrices
8.3 Nonnegative matrices
8.4 Irreducible nonnegative matrices
8.5 Primitive matrices
8.6 A general limit theorem
8.7 Stochastic and doubly stochastic matrices
Appendix A Complex Numbers
Appendix B Convex Sets and Functions
Appendix C The Fundamental Theorem of Algebra
Appendix D Continuity of Polynomial Zeroes and Matrix Eigenvalues
Appendix E Continuity, Compactness, andWeierstrass’s Theorem
Appendix F Canonical Pairs
References
Notation
Hints for Problems
Index
