Discrete Mathematics with Proof / Edition 2

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Overview

A Trusted Guide to Discrete Mathematics with Proof? Now in a Newly Revised Edition

Discrete mathematics has become increasingly popular in recent years due to its growing applications in the field of computer science. Discrete Mathematics with Proof, Second Edition continues to facilitate an up-to-date understanding of this important topic, exposing readers to a wide range of modern and technological applications.

The book begins with an introductory chapter that provides an accessible explanation of discrete mathematics. Subsequent chapters explore additional related topics including counting, finite probability theory, recursion, formal models in computer science, graph theory, trees, the concepts of functions, and relations. Additional features of the Second Edition include:

  • An intense focus on the formal settings of proofs and their techniques, such as constructive proofs, proof by contradiction, and combinatorial proofs
  • New sections on applications of elementary number theory, multidimensional induction, counting tulips, and the binomial distribution
  • Important examples from the field of computer science presented as applications including the Halting problem, Shannon's mathematical model of information, regular expressions, XML, and Normal Forms in relational databases
  • Numerous examples that are not often found in books on discrete mathematics including the deferred acceptance algorithm, the Boyer-Moore algorithm for pattern matching, Sierpinski curves, adaptive quadrature, the Josephus problem, and the five-color theorem
  • Extensive appendices that outline supplemental material on analyzing claims and writing mathematics, along with solutions to selected chapter exercises

Combinatorics receives a full chapter treatment that extends beyond the combinations and permutations material by delving into non-standard topics such as Latin squares, finite projective planes, balanced incomplete block designs, coding theory, partitions, occupancy problems, Stirling numbers, Ramsey numbers, and systems of distinct representatives. A related Web site features animations and visualizations of combinatorial proofs that assist readers with comprehension. In addition, approximately 500 examples and over 2,800 exercises are presented throughout the book to motivate ideas and illustrate the proofs and conclusions of theorems.

Assuming only a basic background in calculus, Discrete Mathematics with Proof, Second Edition is an excellent book for mathematics and computer science courses at the undergraduate level. It is also a valuable resource for professionals in various technical fields who would like an introduction to discrete mathematics.

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Product Details

  • ISBN-13: 9780470457931
  • Publisher: Wiley, John & Sons, Incorporated
  • Publication date: 6/22/2009
  • Edition description: New Edition
  • Edition number: 2
  • Pages: 928
  • Sales rank: 1,371,988
  • Product dimensions: 8.40 (w) x 10.00 (h) x 2.10 (d)

Meet the Author

Eric Gossett, PhD, is Professor of Mathematics and Computer Science at Bethel University. Dr. Gossett has thirty years of academic and industry experience in the areas of Web programming, discrete mathematics, data structures, linear algebra, and algebraic structures. He is the recipient of the Bethel Faculty Service Award for his work developing Bethel's first generation of Web services.

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Table of Contents

Preface.

Acknowledgments.

To The Student.

1 Introduction.

1.1 What Is Discrete Mathematics?

1.2 The Stable Marriage Problem.

1.3 Other Examples.

1.4 Exercises.

1.5 Chapter Review.

2 Sets, Logic, and Boolean Algebras.

2.1 Sets.

2.2 Logic in Daily Life.

2.3 Propositional Logic.

2.4 Logical Equivalence and Rules of Inference.

2.5 Boolean Algebras.

2.6 Predicate Logic.

2.7 Quick Check Solutions.

2.8 Chapter Review.

3 Proof.

3.1 Introduction to Mathematical Proof.

3.2 Elementary Number Theory: Fuel for Practice.

3.3 Proof Strategies.

3.4 Applications of Elementary Number Theory.

3.5 Mathematical Induction.

3.6 Creating Proofs: Hints and Suggestions.

3.7 Quick Check Solutions.

3.8 Chapter Review.

4 Algorithms.

4.1 Expressing Algorithms.

4.2 Measuring Algorithm Efficiency.

4.3 Pattern Matching.

4.4 The Halting Problem.

4.5 Quick Check Solutions.

4.6 Chapter Review.

5 Counting.

5.1 Permutations and Combinations.

5.2 Combinatorial Proofs.

5.3 Pigeon-Hole Principle; Inclusion-Exclusion.

5.4 Quick Check Solutions.

5.5 Chapter Review.

6 Finite Probability Theory.

6.1 The Language of Probabilities.

6.2 Conditional Probabilities and Independent Events.

6.3 Counting and Probability.

6.4 Expected Value.

6.5 The Binomial Distribution.

6.6 Bayes’s Theorem.

6.7 Quick Check Solutions.

7 Recursion.

7.1 Recursive Algorithms.

7.2 Recurrence Relations.

7.3 Big-Θ and Recursive Algorithms: The Master Theorem.

7.4 Generating Functions.

7.5 The Josephus Problem.

7.6 Quick Check Solutions.

7.7 Chapter Review.

8 Combinatorics.

8.1 Partitions, Occupancy Problems, Stirling Numbers.

8.2 Latin Squares; Finite Projective Planes.

8.3 Balanced Incomplete Block Designs.

8.4 The Knapsack Problem.

8.5 Error-Correcting Codes.

8.6 Distinct Representatives, Ramsey Numbers.

8.7 Quick Check Solutions.

8.8 Chapter Review.

9 Formal Models in Computer Science.

9.1 Information.

9.2 Finite-State Machines.

9.3 Formal Languages.

9.4 Regular Expressions.

9.5 The Three Faces of Regular.

9.6 A Glimpse at More Advanced Topics.

9.7 Quick Check Solutions.

9.8 Chapter Review.

10. Graphs.

10.1 Terminology.

10.2 Connectivity and Adjacency.

10.3 Euler and Hamilton.

10.4 Representation and Isomorphism.

10.5 The Big Theorems: Planarity, Euler, Polyhedra, Chromatic Number.

10.6 Directed Graphs and Weighted Graphs.

10.7 Quick Check Solutions.

10.8 Chapter Review.

11 Trees.

11.1 Terminology, Counting.

11.2 Traversal, Searching, and Sorting.

11.3 More Applications of Trees.

11.4 Spanning Trees.

11.5 Quick Check Solutions.

11.6 Chapter Review.

12 Functions, Relations, Databases, and Circuits.

12.1 Functions and Relations.

12.2 Equivalence Relations, Partially Ordered Sets.

12.3 n-ary Relations and Relational Databases.

12.4 Boolean Functions and Boolean Expressions.

12.5 Combinatorial Circuits.

12.6 Quick Check Solutions.

12.7 Chapter Review.

A. Number Systems.

A.1 The Natural Numbers.

A.2 The Integers.

A.3 The Rational Numbers.

A.4 The Real Numbers.

A.5 The Complex Numbers.

A.6 Other Number Systems.

A.7 Representation of Numbers.

B. Summation Notation.

C. Logic Puzzles and Analyzing Claims.

C.1 Logic Puzzles.

C.2 Analyzing Claims.

C.3 Quick Check Solutions.

D. The Golden Ratio.

E. Matrices.

F. The Greek Alphabet.

G. Writing Mathematics.

H. Solutions to Selected Exercises.

H.1 Introduction.

H.2 Sets, Logic, and Boolean Algebras.

H.3 Proof.

H.4 Algorithms.

H.5 Counting.

H.6 Finite Probability Theory.

H.7 Recursion.

H.8 Combinatorics.

H.9 Formal Models in Computer Science.

H.10 Graphs.

H.11 Trees.

H.12 Functions, Relations, Databases, and Circuits.

H.13 Appendices.

Bibliography.

Index.

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Sort by: Showing 1 Customer Reviews
  • Posted November 11, 2009

    more from this reviewer

    intersection of pure maths and computer science

    Gossett's book is directed at the intersection of 2 disciplines - pure mathematics and computer science. Students of the former are used to strict expositions based on rigourous unfoldings of logic, usually held together by fiducial markers called theorems. CS students typically have had texts that played a little looser, indulging in some handwaving.

    For the present reader, you get the strict logic. And the understanding that all CS is built on the conceptual foundations of discrete maths. The book deliberately starts off easily, with set and logic concepts you may have encountered in high school. Number theory is then quickly built up. Seminal results like the Chinese Remainder Theorem and Bayes Theorem are explained. You should appreciate that a CS education also involves a good understanding of probability.

    The book is long, but it has limits and you should understand what those are. Gossett goes up to the boundaries of information theory, by mentioning some of the base concepts in it. Claude Shannon gets a brief mention. However, to keep the book's length tractable, it foreswears off any deeper foray into this vast and fascinating field.

    Ditto for cryptography. Number theory is its underpinning. But only a quick summary is given of important cryptographic methods. Public key infrastructure and RSA are profiled in a mere 2 pages. Note however that the descriptions given in those pages are as concise and understandable as anything you are likely to read at this level.

    As a practical matter, if the book whets your appetite for information theory or cryptography, that is all to the good. It gives you a solid basis for serious study of them, and there are a plentitude of other texts devoted to those subjects. (Cf.

    Gossett also supplies many problems for each chapter of his book, making it suitable as the main text for an undergraduate course. The level of difficulty varies. Some problems are trivial, while others get quite involved.

    The algorithms in the book do not rise to the intricacy of Knuth's classic Art of Computer Programming, The, Volumes 1-3 Boxed Set (2nd Edition) (Vol 1-3). But those books are quite forbidding for many undergrads. Gossett's text is a more realistic choice.

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