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Graphs and Matrices 2011. Copublication with the Hindustan Book Agency [Minkštas viršelis]

  • Formatas: Paperback / softback, 171 pages, aukštis x plotis: 235x155 mm, weight: 291 g, IX, 171 p., 1 Paperback / softback
  • Serija: Universitext
  • Išleidimo metai: 30-Dec-2010
  • Leidėjas: Springer London Ltd
  • ISBN-10: 1848829809
  • ISBN-13: 9781848829800
Kitos knygos pagal šią temą:
  • Formatas: Paperback / softback, 171 pages, aukštis x plotis: 235x155 mm, weight: 291 g, IX, 171 p., 1 Paperback / softback
  • Serija: Universitext
  • Išleidimo metai: 30-Dec-2010
  • Leidėjas: Springer London Ltd
  • ISBN-10: 1848829809
  • ISBN-13: 9781848829800
Kitos knygos pagal šią temą:
Whilst it is a moot point amongst researchers, linear algebra is an important component in the study of graphs. This book illustrates the elegance and power of matrix techniques in the study of graphs by means of several results, both classical and recent. The emphasis on matrix techniques is greater than other standard references on algebraic graph theory, and the important matrices associated with graphs such as incidence, adjacency and Laplacian matrices are treated in detail.

Presenting a useful overview of selected topics in algebraic graph theory, early chapters of the text focus on regular graphs, algebraic connectivity, the distance matrix of a tree and its generalized version for arbitrary graphs, known as the resistance matrix. Coverage of later topics include Laplacian eigenvalues of threshold graphs, the positive definite completion problem and matrix games based on a graph.

Such an extensive coverage of the subject area provides a welcome prompt for further exploration, and the inclusion of exercises enables practical learning throughout the book. It may also be applied to a selection of sub-disciplines within science and engineering.

Whilst this book will be invaluable to students and researchers in graph theory and combinatorial matrix theory who want to be acquainted with matrix theoretic ideas used in graph theory, it will also benefit a wider, cross-disciplinary readership.

Recenzijos

From the reviews:

Students who have completed introductory courses in linear algebra and graph theory should be able to understand and benefit from this book. It is divided into 12 chapters. Each chapter includes a good number of references in a bibliographic format. A complete bibliography with all of the chapter references is available at the end of the book. Summing Up: Recommended. Upper-division undergraduates through researchers/faculty. (J. T. Saccoman, Choice, Vol. 49 (1), September, 2011)

The book is a study of matrices associated to graphs based on linear algebra techniques. The exposition is exact and clear. The proofs are presented in detail and should be understood with no difficulty by any reader with a preliminary background in linear algebra. Hence, the book can be used as a textbook for undergraduate level courses. Graduate students and researchers working on spectral graph theory or closely related fields will also benefit from the book. (Behruz Tayfeh-Rezaie, Mathematical Reviews, Issue 2012 f)

A student having completed introductory courses in Linear Algebra and Graph Theory should be able to understand and benefit from this text. At the end of each of the twelve chapters there are a few exercises and a good number of references. this text would be a fine resource for an advanced undergraduate or someone wishing to learn more about this synergistic field of study. (John T. Saccoman, The Mathematical Association of America, June, 2011)

Preface v
1 Preliminaries
1(10)
1.1 Matrices
1(4)
1.2 Eigenvalues of symmetric matrices
5(2)
1.3 Generalized inverses
7(2)
1.4 Graphs
9(2)
2 Incidence Matrix
11(14)
2.1 Rank
12(1)
2.2 Minors
13(2)
2.3 Path matrix
15(1)
2.4 Integer generalized inverses
16(1)
2.5 Moore-Penrose inverse
17(2)
2.6 0---1 Incidence matrix
19(2)
2.7 Matchings in bipartite graphs
21(4)
3 Adjacency Matrix
25(20)
3.1 Eigenvalues of some graphs
26(2)
3.2 Determinant
28(3)
3.3 Bounds
31(5)
3.4 Energy of a graph
36(1)
3.5 Antiadjacency matrix of a directed graph
37(2)
3.6 Nonsingular trees
39(6)
4 Laplacian Matrix
45(12)
4.1 Basic properties
46(1)
4.2 Computing Laplacian eigenvalues
47(1)
4.3 Matrix-tree theorem
48(2)
4.4 Bounds for Laplacian spectral radius
50(1)
4.5 Edge-Laplacian of a tree
51(6)
5 Cycles and Cuts
57(8)
5.1 Fundamental cycles and fundamental cuts
57(2)
5.2 Fundamental matrices
59(1)
5.3 Minors
60(5)
6 Regular Graphs
65(16)
6.1 Perron-Frobenius theory
65(5)
6.2 Adjacency algebra of a regular graph
70(1)
6.3 Complement and line graph of a regular graph
70(3)
6.4 Strongly regular graphs and friendship theorem
73(3)
6.5 Graphs with maximum energy
76(5)
7 Algebraic Connectivity
81(14)
7.1 Preliminary results
81(2)
7.2 Classification of trees
83(5)
7.3 Monotonicity properties of Fiedler vector
88(1)
7.4 Bounds for algebraic connectivity
89(6)
8 Distance Matrix of a Tree
95(16)
8.1 Distance matrix of a graph
96(3)
8.2 Distance matrix and Laplacian of a tree
99(5)
8.3 Eigenvalues of the distance matrix of a tree
104(7)
9 Resistance Distance
111(14)
9.1 The triangle inequality
112(1)
9.2 Network flows
113(3)
9.3 A random walk on graphs
116(2)
9.4 Effective resistance in electrical networks
118(1)
9.5 Resistance matrix
119(6)
10 Laplacian Eigenvalues of Threshold Graphs
125(12)
10.1 Majorization
125(4)
10.2 Threshold graphs
129(2)
10.3 Spectral integral variation
131(6)
11 Positive Definite Completion Problem
137(8)
11.1 Nonsingular completion
137(1)
11.2 Chordal graphs
138(2)
11.3 Positive definite completion
140(5)
12 Matrix Games Based on Graphs
145(14)
12.1 Matrix games
145(2)
12.2 Vertex selection games
147(1)
12.3 Tournament games
148(3)
12.4 Incidence matrix games
151(8)
Hints and Solutions to Selected Exercises 159(6)
Bibliography 165(4)
Index 169