Muutke küpsiste eelistusi

E-raamat: Matrix Theory

Teised raamatud teemal:
  • Formaat - PDF+DRM
  • Hind: 86,19 €*
  • * hind on lõplik, st. muud allahindlused enam ei rakendu
  • Lisa ostukorvi
  • Lisa soovinimekirja
  • See e-raamat on mõeldud ainult isiklikuks kasutamiseks. E-raamatuid ei saa tagastada.
Teised raamatud teemal:

DRM piirangud

  • Kopeerimine (copy/paste):

    ei ole lubatud

  • Printimine:

    ei ole lubatud

  • Kasutamine:

    Digitaalõiguste kaitse (DRM)
    Kirjastus on väljastanud selle e-raamatu krüpteeritud kujul, mis tähendab, et selle lugemiseks peate installeerima spetsiaalse tarkvara. Samuti peate looma endale  Adobe ID Rohkem infot siin. E-raamatut saab lugeda 1 kasutaja ning alla laadida kuni 6'de seadmesse (kõik autoriseeritud sama Adobe ID-ga).

    Vajalik tarkvara
    Mobiilsetes seadmetes (telefon või tahvelarvuti) lugemiseks peate installeerima selle tasuta rakenduse: PocketBook Reader (iOS / Android)

    PC või Mac seadmes lugemiseks peate installima Adobe Digital Editionsi (Seeon tasuta rakendus spetsiaalselt e-raamatute lugemiseks. Seda ei tohi segamini ajada Adober Reader'iga, mis tõenäoliselt on juba teie arvutisse installeeritud )

    Seda e-raamatut ei saa lugeda Amazon Kindle's. 

Matrix theory is a classical topic of algebra that had originated, in its current form, in the middle of the 19th century. It is remarkable that for more than 150 years it continues to be an active area of research full of new discoveries and new applications.

This book presents modern perspectives of matrix theory at the level accessible to graduate students. It differs from other books on the subject in several aspects. First, the book treats certain topics that are not found in the standard textbooks, such as completion of partial matrices, sign patterns, applications of matrices in combinatorics, number theory, algebra, geometry, and polynomials. There is an appendix of unsolved problems with their history and current state. Second, there is some new material within traditional topics such as Hopf's eigenvalue bound for positive matrices with a proof, a proof of Horn's theorem on the converse of Weyl's theorem, a proof of Camion-Hoffman's theorem on the converse of the diagonal dominance theorem, and Audenaert's elegant proof of a norm inequality for commutators. Third, by using powerful tools such as the compound matrix and Grobner bases of an ideal, much more concise and illuminating proofs are given for some previously known results. This makes it easier for the reader to gain basic knowledge in matrix theory and to learn about recent developments.

Arvustused

There are plenty of exercises to be had, and the authors goal is clearly to guide able and willing graduate students toward research in this area I think Zhan will be successful in this enterprise: its a very nice book indeed. -- MAA

Preface ix
Chapter 1 Preliminaries
1(34)
§1.1 Classes of Special Matrices
2(4)
§1.2 The Characteristic Polynomial
6(2)
§1.3 The Spectral Mapping Theorem
8(1)
§1.4 Eigenvalues and Diagonal Entries
8(2)
§1.5 Norms
10(3)
§1.6 Convergence of the Power Sequence of a Matrix
13(1)
§1.7 Matrix Decompositions
14(4)
§1.8 Numerical Range
18(3)
§1.9 The Companion Matrix of a Polynomial
21(1)
§1.10 Generalized Inverses
22(1)
§1.11 Schur Complements
23(1)
§1.12 Applications of Topological Ideas
24(1)
§1.13 Grobner Bases
25(2)
§1.14 Systems of Linear Inequalities
27(2)
§1.15 Orthogonal Projections and Reducing Subspaces
29(2)
§1.16 Books and Journals about Matrices
31(4)
Exercises
31(4)
Chapter 2 Tensor Products and Compound Matrices
35(16)
§2.1 Definitions and Basic Properties
35(5)
§2.2 Linear Matrix Equations
40(4)
§2.3 Frobenius-Konig Theorem
44(2)
§2.4 Compound Matrices
46(5)
Exercises
49(2)
Chapter 3 Hermitian Matrices and Majorization
51(26)
§3.1 Eigenvalues of Hermitian Matrices
51(5)
§3.2 Majorization and Doubly Stochastic Matrices
56(12)
§3.3 Inequalities for Positive Semidefinite Matrices
68(9)
Exercises
74(3)
Chapter 4 Singular Values and Unitarily Invariant Norms
77(26)
§4.1 Singular Values
77(11)
§4.2 Symmetric Gauge Functions
88(2)
§4.3 Unitarily Invariant Norms
90(7)
§4.4 The Cartesian Decomposition of Matrices
97(6)
Exercises
100(3)
Chapter 5 Perturbation of Matrices
103(16)
§5.1 Eigenvalues
103(9)
§5.2 The Polar Decomposition
112(2)
§5.3 Norm Estimation of Band Parts
114(2)
§5.4 Backward Perturbation Analysis
116(3)
Exercises
118(1)
Chapter 6 Nonnegative Matrices
119(30)
§6.1 Perron-Frobenius Theory
120(12)
§6.2 Matrices and Digraphs
132(2)
§6.3 Primitive and Imprimitive Matrices
134(4)
§6.4 Special Classes of Nonnegative Matrices
138(4)
§6.5 Two Theorems about Positive Matrices
142(7)
Exercises
147(2)
Chapter 7 Completion of Partial Matrices
149(16)
§7.1 Friedland's Theorem about Diagonal Completions
150(3)
§7.2 Farahat-Ledermann's Theorem about Borderline Completions
153(4)
§7.3 Parrott's Theorem about Norm-Preserving Completions
157(2)
§7.4 Positive Definite Completions
159(6)
Chapter 8 Sign Patterns
165(16)
§8.1 Sign-Nonsingular Patterns
168(1)
§8.2 Eigenvalues
169(4)
§8.3 Sign Semi-Stable Patterns
173(1)
§8.4 Sign Patterns Allowing a Positive Inverse
174(7)
Exercises
179(2)
Chapter 9 Miscellaneous Topics
181(32)
§9.1 Similarity of Real Matrices via Complex Matrices
181(1)
§9.2 Inverses of Band Matrices
182(2)
§9.3 Norm Bounds for Commutators
184(4)
§9.4 The Converse of the Diagonal Dominance Theorem
188(4)
§9.5 The Shape of the Numerical Range
192(5)
§9.6 An Inversion Algorithm
197(1)
§9.7 Canonical Forms for Similarity
198(9)
§9.8 Extremal Sparsity of the Jordan Canonical Form
207(6)
Chapter 10 Applications of Matrices
213(14)
§10.1 Combinatorics
214(2)
§10.2 Number Theory
216(1)
§10.3 Algebra
217(3)
§10.4 Geometry
220(2)
§10.5 Polynomials
222(5)
Unsolved Problems 227(10)
Bibliography 237(12)
Notation 249(2)
Index 251
Xingzhi Zhan, East China Normal University, Shanghai, China.