About this product

Product Identifiers

PublisherDover Publications, Incorporated

ISBN-100486691152

ISBN-139780486691152

eBay Product ID (ePID)961798

Product Key Features

Number of Pages256 Pages

Publication NameIntroductory Discrete Mathematics

LanguageEnglish

Publication Year2010

SubjectRéférence, Discrete Mathematics

TypeTextbook

AuthorV. K. Balakrishnan

Subject AreaMathematics

SeriesDover Books on Computer Science Ser.

FormatTrade Paperback

Dimensions

Item Height0.5 in

Item Weight13.2 Oz

Item Length9.2 in

Item Width6.5 in

Additional Product Features

Intended AudienceCollege Audience

LCCN95-052384

Dewey Edition20

IllustratedYes

Dewey Decimal511

Table Of ContentPreface 0 Set Theory and Logic 0.1 Introduction to Set Theory 0.2 Functions and Relations 0.3 Inductive Proofs and Recursive Definitions 0.4 The Language of Logic 0.5 Notes and References 0.6 Exercises 1 Combinatorics 1.1 Two Basic Counting Rules 1.2 Permutations 1.3 Combinations 1.4 More on Permutations and Combinations 1.5 The Pigeonhole Principle 1.6 The Inclusion-Exclusion Principle 1.7 Summary of Results in Combinatorics 1.8 Notes and References 1.9 Exercises 2 Generating Functions 2.1 Introduction 2.2 Ordinary Generating Functions 2.3 Exponential Generating Functions 2.4 Notes and References 2.5 Exercises 3 Recurrence Relations 3.1 Introduction 3.2 Homogeneous Recurrence Relations 3.3 Inhomogeneous Recurrence Relations 3.4 Recurrence Relations and Generating Functions 3.5 Analysis of Alogorithms 3.6 Notes and References 3.7 Exercises 4 Graphs and Digraphs 4.1 Introduction 4.2 Adjacency Matrices and Incidence Matrices 4.3 Joining in Graphs 4.4 Reaching in Digraphs 4.5 Testing Connectedness 4.6 Strong Orientation of Graphs 4.7 Notes and References 4.8 Exercises 5 More on Graphs and Digraphs 5.1 Eulerian Paths and Eulerian Circuits 5.2 Coding and de Bruijn Digraphs 5.3 Hamiltonian Paths and Hamiltonian Cycles 5.4 Applications of Hamiltonian Cycles 5.5 Vertex Coloring and Planarity of Graphs 5.6 Notes and References 5.7 Exercises 6 Trees and Their Applications 6.1 Definitions and Properties 6.2 Spanning Trees 6.3 Binary Trees 6.4 Notes and References 6.5 Exercises 7 Spanning Tree Problems 7.1 More on Spanning Trees 7.2 Kruskal's Greedy Algorithm 7.3 Prim's Greedy Algorithm 7.4 Comparison of the Two Algorithms 7.5 Notes and References 7.6 Exercises 8 Shortest Path Problems 8.1 Introduction 8.2 Dijkstra's Algorithm 8.3 Floyd-Warshall Algorithm 8.4 Comparison of the Two Algorithms 8.5 Notes and References 8.6 Exercises Appendix What is NP-Completeness? A.1 Problems and Their Instances A.2 The Size of an Instance A.3 Algorithm to Solve a Problem A.4 Complexity of an Algorithm A.5 "The "Big Oh" or the O(·) Notation" A.6 Easy Problems and Difficult Problems A.7 The Class P and the Class NP A.8 Polynomial Transformations and NP-Completeness A.9 Coping with Hard Problems Bibliography Answers to Selected Exercises Index

Edition DescriptionReprint,New Edition

SynopsisConcise, undergraduate-level text focuses on combinatorics, graph theory with applications to some standard network optimization problems, and algorithms to solve these problems. Applications are emphasized and more than 200 exercises help students test their grasp of the material. Appendix. Bibliography. Answers to Selected Exercises., This concise, undergraduate-level text focuses on combinatorics, graph theory with applications to some standard network optimization problems, and algorithms. More than 200 exercises, many with complete solutions. 1991 edition., This concise, undergraduate-level text focuses on combinatorics, graph theory with applications to some standard network optimization problems, and algorithms. Geared toward mathematics and computer science majors, it emphasizes applications, offering more than 200 exercises to help students test their grasp of the material and providing answers to selected exercises. 1991 edition., This concise text offers an introduction to discrete mathematics for undergraduate students in computer science and mathematics. Mathematics educators consider it vital that their students be exposed to a course in discrete methods that introduces them to combinatorial mathematics and to algebraic and logical structures focusing on the interplay between computer science and mathematics. The present volume emphasizes combinatorics, graph theory with applications to some stand network optimization problems, and algorithms to solve these problems. Chapters 03 cover fundamental operations involving sets and the principle of mathematical induction, and standard combinatorial topics: basic counting principles, permutations, combinations, the inclusion-exclusion principle, generating functions, recurrence relations, and an introduction to the analysis of algorithms. Applications are emphasized wherever possible and more than 200 exercises at the ends of these chapters help students test their grasp of the material. Chapters 4 and 5 survey graphs and digraphs, including their connectedness properties, applications of graph coloring, and more, with stress on applications to coding and other related problems. Two important problems in network optimization the minimal spanning tree problem and the shortest distance problem are covered in the last two chapters. A very brief nontechnical exposition of the theory of computational complexity and NP-completeness is outlined in the appendix., This concise text offers an introduction to discrete mathematics for undergraduate students in computer science and mathematics. Mathematics educators consider it vital that their students be exposed to a course in discrete methods that introduces them to combinatorial mathematics and to algebraic and logical structures focusing on the interplay between computer science and mathematics. The present volume emphasizes combinatorics, graph theory with applications to some stand network optimization problems, and algorithms to solve these problems. Chapters 0-3 cover fundamental operations involving sets and the principle of mathematical induction, and standard combinatorial topics: basic counting principles, permutations, combinations, the inclusion-exclusion principle, generating functions, recurrence relations, and an introduction to the analysis of algorithms. Applications are emphasized wherever possible and more than 200 exercises at the ends of these chapters help students test their grasp of the material. Chapters 4 and 5 survey graphs and digraphs, including their connectedness properties, applications of graph coloring, and more, with stress on applications to coding and other related problems. Two important problems in network optimization the minimal spanning tree problem and the shortest distance problem are covered in the last two chapters. A very brief nontechnical exposition of the theory of computational complexity and NP-completeness is outlined in the appendix.

LC Classification NumberQA39.2.B35