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Foundations of Algorithms, Fourth Edition

Author(s): Richard Neapolitan, PhD, Northeastern Illinois University, Illinois
Kumarss Naimipour, Northeastern Illinois University, Illinois
Details:
  • ISBN-13: 9780763782504
  • Hardcover    627 pages      © 2011
Price: International Sales $139.95 US List
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Overview

Foundations of Algorithms, Fourth Edition offers a well-balanced presentation of algorithm design, complexity analysis of algorithms, and computational complexity. The volume is accessible to mainstream computer science students who have a background in college algebra and discrete structures. To support their approach, the authors present mathematical concepts using standard English and a simpler notation than is found in most texts. A review of essential mathematical concepts is presented in three appendices. The authors also reinforce the explanations with numerous concrete examples to help students grasp theoretical concepts.

ShowKey Features

Makes use of C++ and Java pseudocode helping students better understand complex algorithms.

A chapter on numerical algorithms includes a review of basic number theory, Euclid's Algorithm for finding the greatest common divisor, a review of modular arithmetic, an algorithm for solving modular linear equations, an algorithm for computing modular powers, and the new polynomial-time algorithm for determining whether a number is prime.

Students are not required to have a calculus background.  College algebra and discrete structures are prerequisite for the text.

Contains numerous examples throughout, ensuring that students have a clear grasp of the complex algorithms being discussed.

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ShowTable of Contents

Preface  
Chapter  1  Algorithms: Efficiency, Analysis, and Order
Chapter  2  Divide-and-Conquer
Chapter  3  Dynamic Programming
Chapter  4  The Greedy Approach
Chapter  5  Backtracking
Chapter  6  Branch-and-Bound
Chapter  7  Introduction to Computational Complexity: The Sorting Problem
Chapter  8  More Computational Complexity: The Searching Problem
Chapter  9  Computational Complexity and Intractability: An Introduction to the Theory of NP
Chapter  10  Number-Theoretic Algorithms
Chapter  11  Introduction to Parallel Algorithms
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ShowAbout the Author(s)

Richard Neapolitan, PhD-Northeastern Illinois University, Illinois


Richard Neapolitan has been a researcher in the area of uncertainty in artificial intelligence, in particular Bayesian networks, since the mid 1980's. In 1990 he wrote the seminal text Probabilistic Reasoning in Expert Systems, which helped to unify the field of Bayesian network. Dr. Neapolitan established the field further with his book Learning Bayesian Network, which appeared in 2003. Besides authoring books, Dr. Neapolitan has published numerous cross-disciplinary articles spanning the fields of computer science, mathematics, philosophy of science, and psychology. His current research interests includes the comparison of human reasoning to normative models and the development of hybrid models. Presently, he is professor and chair of Computer Science at Northeastern Illinois University, while also serving as a visiting scholar at Monash University in Australia.

Kumarss Naimipour-Northeastern Illinois University, Illinois

Kumarss Naimipour is an Associate Professor in the Computer Science Department at Northeastern Illinois University.    In 1992, he received his Ph.D. in Computer Science/Applied Mathematics from the University of Illinois at Chicago, where he taught courses in computer science and mathematics. Since joining Northeastern Illinois University in 1988, he has published several articles in professional journals and conference proceedings, and has taught different topics in computer science and mathematics. Dr. Naimipour received the Faculty Excellence Award from Northeastern Illinois University in 1994, and was also selected for inclusion in the Seventh Edition of Who's Who Among America's Teachers in 2002. 

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