Atjaunināt sīkdatņu piekrišanu

Concise Text on Advanced Linear Algebra [Mīkstie vāki]

  • Formāts: Paperback / softback, 331 pages, height x width x depth: 228x152x20 mm, weight: 490 g, Worked examples or Exercises
  • Izdošanas datums: 04-Dec-2014
  • Izdevniecība: Cambridge University Press
  • ISBN-10: 1107456819
  • ISBN-13: 9781107456815
Citas grāmatas par šo tēmu:
  • Mīkstie vāki
  • Cena: 52,11 €
  • Grāmatu piegādes laiks ir 3-4 nedēļas, ja grāmata ir uz vietas izdevniecības noliktavā. Ja izdevējam nepieciešams publicēt jaunu tirāžu, grāmatas piegāde var aizkavēties.
  • Daudzums:
  • Ielikt grozā
  • Piegādes laiks - 4-6 nedēļas
  • Pievienot vēlmju sarakstam
  • Formāts: Paperback / softback, 331 pages, height x width x depth: 228x152x20 mm, weight: 490 g, Worked examples or Exercises
  • Izdošanas datums: 04-Dec-2014
  • Izdevniecība: Cambridge University Press
  • ISBN-10: 1107456819
  • ISBN-13: 9781107456815
Citas grāmatas par šo tēmu:
This engaging textbook for advanced undergraduate students and beginning graduates covers the core subjects in linear algebra. The author motivates the concepts by drawing clear links to applications and other important areas, such as differential topology and quantum mechanics. The book places particular emphasis on integrating ideas from analysis wherever appropriate. For example, the notion of determinant is shown to appear from calculating the index of a vector field which leads to a self-contained proof of the Fundamental Theorem of Algebra, and the Cayley–Hamilton theorem is established by recognizing the fact that the set of complex matrices of distinct eigenvalues is dense. The material is supplemented by a rich collection of over 350 mostly proof-oriented exercises, suitable for students from a wide variety of backgrounds. Selected solutions are provided at the back of the book, making it suitable for self-study as well as for use as a course text.

An engaging textbook for advanced undergraduate students and beginning graduates covering the core subjects in linear algebra. The author clearly motivates the theory to give readers a thorough grasp of the concepts and draws clear links to applications in mathematics and beyond.

Papildus informācija

This engaging, well-motivated textbook helps advanced undergraduate students to grasp core concepts and reveals applications in mathematics and beyond.
Preface ix
Notation and convention xiii
1 Vector spaces
1(33)
1.1 Vector spaces
1(7)
1.2 Subspaces, span, and linear dependence
8(5)
1.3 Bases, dimensionality, and coordinates
13(3)
1.4 Dual spaces
16(4)
1.5 Constructions of vector spaces
20(5)
1.6 Quotient spaces
25(3)
1.7 Normed spaces
28(6)
2 Linear mappings
34(44)
2.1 Linear mappings
34(11)
2.2 Change of basis
45(5)
2.3 Adjoint mappings
50(3)
2.4 Quotient mappings
53(2)
2.5 Linear mappings from a vector space into itself
55(15)
2.6 Norms of linear mappings
70(8)
3 Determinants
78(37)
3.1 Motivational examples
78(10)
3.2 Definition and properties of determinants
88(14)
3.3 Adjugate matrices and Cramer's rule
102(5)
3.4 Characteristic polynomials and Cayley-Hamilton theorem
107(8)
4 Scalar products
115(32)
4.1 Scalar products and basic properties
115(5)
4.2 Non-degenerate scalar products
120(7)
4.3 Positive definite scalar products
127(10)
4.4 Orthogonal resolutions of vectors
137(5)
4.5 Orthogonal and unitary versus isometric mappings
142(5)
5 Real quadratic forms and self-adjoint mappings
147(33)
5.1 Bilinear and quadratic forms
147(4)
5.2 Self-adjoint mappings
151(6)
5.3 Positive definite quadratic forms, mappings, and matrices
157(7)
5.4 Alternative characterizations of positive definite matrices
164(6)
5.5 Commutativity of self-adjoint mappings
170(2)
5.6 Mappings between two spaces
172(8)
6 Complex quadratic forms and self-adjoint mappings
180(25)
6.1 Complex sesquilinear and associated quadratic forms
180(4)
6.2 Complex self-adjoint mappings
184(4)
6.3 Positive definiteness
188(6)
6.4 Commutative self-adjoint mappings and consequences
194(5)
6.5 Mappings between two spaces via self-adjoint mappings
199(6)
7 Jordan decomposition
205(21)
7.1 Some useful facts about polynomials
205(3)
7.2 Invariant subspaces of linear mappings
208(3)
7.3 Generalized eigenspaces as invariant subspaces
211(7)
7.4 Jordan decomposition theorem
218(8)
8 Selected topics
226(22)
8.1 Schur decomposition
226(4)
8.2 Classification of skewsymmetric bilinear forms
230(7)
8.3 Perron-Frobenius theorem for positive matrices
237(5)
8.4 Markov matrices
242(6)
9 Excursion: Quantum mechanics in a nutshell
248(19)
9.1 Vectors in CN and Dirac bracket
248(4)
9.2 Quantum mechanical postulates
252(5)
9.3 Non-commutativity and uncertainty principle
257(5)
9.4 Heisenberg picture for quantum mechanics
262(5)
Solutions to selected exercises 267(44)
Bibliographic notes 311(2)
References 313(2)
Index 315
Yisong Yang is Professor of Mathematics at the Polytechnic School of Engineering, New York University. His areas of research are partial differential equations and mathematical physics. He is a Fellow of the American Mathematical Society and the author of Solitons in Field Theory and Nonlinear Analysis (2001).