Discrete Mathematics

by Johnsonbaugh, Richard

• ISBN13: 9780321985835
• ISBN10: 0321985834
• Edition: 8th
• Format: Loose-leaf
• Copyright: 2017-04-14
• Publisher: Pearson

Summary

NOTE: This edition features the same content as the traditional text in a convenient, three-hole-punched, loose-leaf version. Books a la Carte also offer a great value; this format costs significantly less than a new textbook. Before purchasing, check with your instructor or review your course syllabus to ensure that you select the correct ISBN. For Books a la Carte editions that include MyLab™ or Mastering™, several versions may exist for each title – including customized versions for individual schools – and registrations are not transferable. In addition, you may need a Course ID, provided by your instructor, to register for and use MyLab or Mastering products.

For one- or two-term introductory courses in discrete mathematics.

An accessible introduction to the topics of discrete math, this best-selling text also works to expand students’ mathematical maturity.

With nearly 4,500 exercises, Discrete Mathematics provides ample opportunities for students to practice, apply, and demonstrate conceptual understanding. Exercise sets features a large number of applications, especially applications to computer science. The almost 650 worked examples provide ready reference for students as they work. A strong emphasis on the interplay among the various topics serves to reinforce understanding. The text models various problem-solving techniques in detail, then provides opportunity to practice these techniques. The text also builds mathematical maturity by emphasizing how to read and write proofs. Many proofs are illustrated with annotated figures and/or motivated by special Discussion sections. The side margins of the text now include “tiny URLs” that direct students to relevant applications, extensions, and computer programs on the textbook website.

Author Biography

About our author

Richard Johnsonbaugh is Professor Emeritus of Computer Science, Telecommunications and Information Systems, DePaul University, Chicago. Prior to his 20-year service at DePaul University, he was a member and sometime chair of the mathematics departments at Morehouse College and Chicago State University. He has a B.A. degree in mathematics from Yale University, M.A. and Ph.D. degrees in mathematics from the University of Oregon, and an M.S. degree in computer science from the University of Illinois, Chicago. His most recent research interests are in pattern recognition, programming languages, algorithms, and discrete mathematics. He is the author or co-author of numerous books and articles in these areas. Several of his books have been translated into various languages. He is a member of the Mathematical Association of America.

Table of Contents

1. Sets and Logic

1.1 Sets

1.2 Propositions

1.3 Conditional Propositions and Logical Equivalence

1.4 Arguments and Rules of Inference

1.5 Quantifiers

1.6 Nested Quantifiers

Problem-Solving Corner: Quantifiers

2. Proofs

2.1 Mathematical Systems, Direct Proofs, and Counterexamples

2.2 More Methods of Proof

Problem-Solving Corner: Proving Some Properties of Real Numbers

2.3 Resolution Proofs

2.4 Mathematical Induction

Problem-Solving Corner: Mathematical Induction

2.5 Strong Form of Induction and the Well-Ordering Property

3. Functions, Sequences, and Relations

3.1 Functions

Problem-Solving Corner: Functions

3.2 Sequences and Strings

3.3 Relations

3.4 Equivalence Relations

Problem-Solving Corner: Equivalence Relations

3.5 Matrices of Relations

3.6 Relational Databases

4. Algorithms

4.1 Introduction

4.2 Examples of Algorithms

4.3 Analysis of Algorithms

Problem-Solving Corner: Design and Analysis of an Algorithm

4.4 Recursive Algorithms

5. Introduction to Number Theory

5.1 Divisors

5.2 Representations of Integers and Integer Algorithms

5.3 The Euclidean Algorithm

Problem-Solving Corner: Making Postage

5.4 The RSA Public-Key Cryptosystem

6. Counting Methods and the Pigeonhole Principle

6.1 Basic Principles

Problem-Solving Corner: Counting

6.2 Permutations and Combinations

Problem-Solving Corner: Combinations

6.3 Generalized Permutations and Combinations

6.4 Algorithms for Generating Permutations and Combinations

6.5 Introduction to Discrete Probability

6.6 Discrete Probability Theory

6.7 Binomial Coefficients and Combinatorial Identities

6.8 The Pigeonhole Principle

7. Recurrence Relations

7.1 Introduction

7.2 Solving Recurrence Relations

Problem-Solving Corner: Recurrence Relations

7.3 Applications to the Analysis of Algorithms

8. Graph Theory

8.1 Introduction

8.2 Paths and Cycles

Problem-Solving Corner: Graphs

8.3 Hamiltonian Cycles and the Traveling Salesperson Problem

8.4 A Shortest-Path Algorithm

8.5 Representations of Graphs

8.6 Isomorphisms of Graphs

8.7 Planar Graphs

8.8 Instant Insanity

9. Trees

9.1 Introduction

9.2 Terminology and Characterizations of Trees

Problem-Solving Corner: Trees

9.3 Spanning Trees

9.4 Minimal Spanning Trees

9.5 Binary Trees

9.6 Tree Traversals

9.7 Decision Trees and the Minimum Time for Sorting

9.8 Isomorphisms of Trees

9.9 Game Trees

10. Network Models

10.1 Introduction

10.2 A Maximal Flow Algorithm

10.3 The Max Flow, Min Cut Theorem

10.4 Matching

Problem-Solving Corner: Matching

11. Boolean Algebras and Combinatorial Circuits

11.1 Combinatorial Circuits

11.2 Properties of Combinatorial Circuits

11.3 Boolean Algebras

Problem-Solving Corner: Boolean Algebras

11.4 Boolean Functions and Synthesis of Circuits

11.5 Applications

12. Automata, Grammars, and Languages

12.1 Sequential Circuits and Finite-State Machines

12.2 Finite-State Automata

12.3 Languages and Grammars

12.4 Nondeterministic Finite-State Automata

12.5 Relationships Between Languages and Automata

13. Computational Geometry

13.1 The Closest-Pair Problem

13.2 An Algorithm to Compute the Convex Hull

Appendix

A. Matrices

B. Algebra Review

C. Pseudocode

References

Hints and Solutions to Selected Exercises

Index