Algorithms and Theory of Computation Handbook, Volume 1: General Concepts and Techniques

by Mikhail J. Atallah, Marina Blanton

Overview

Algorithms and Theory of Computation Handbook, Second Edition: General Concepts and Techniques provides an up-to-date compendium of fundamental computer science topics and techniques. It also illustrates how the topics and techniques come together to deliver efficient solutions to important practical problems. Along with updating and revising many

Product Details

ISBN-13:	9781040070215
Publisher:	CRC Press
Publication date:	11/20/2009
Series:	Chapman & Hall/CRC Applied Algorithms and Data Structures series
Sold by:	Barnes & Noble
Format:	eBook
Pages:	988
File size:	11 MB
Note:	This product may take a few minutes to download.

About the Author

Mikhail J. Atallah is a distinguished professor of computer science at Purdue University.

Marina Blanton is an assistant professor in the computer science and engineering department at the University of Notre Dame

Table of Contents

Preface, Editors, Contributors, 1 Algorithm Design and Analysis Techniques, 2 Searching, 3 Sorting and Order Statistics, 4 Basic Data Structures, 5 Topics in Data Structures, 6 Multidimensional Data Structures for Spatial Applications, 7 Basic Graph Algorithms, 8 Advanced Combinatorial Algorithms, 9 Dynamic Graph Algorithms, 10 External-Memory Algorithms and Data Structures, 11 Average Case Analysis of Algorithms, 12 Randomized Algorithms, 13 Pattern Matching in Strings, 14 Text Data Compression Algorithms, 15 General Pattern Matching, 16 Computational Number Theory, 17 Algebraic and Numerical Algorithms, 18 Applications of FFT and Structured Matrices, 19 Basic Notions in Computational Complexity, 20 Formal Grammars and Languages, 21 Computability, 22 Complexity Classes, 23 Reducibility and Completeness, 24 Other Complexity Classes and Measures, 25 Parameterized Algorithms, 26 Computational Learning Theory, 27 Algorithmic Coding Theory, 28 Parallel Computation: Models and Complexity Issues, 29 Distributed Computing: A Glimmer of a Theory, 30 Linear Programming, 31 Integer Programming, 32 Convex Optimization, 33 Simulated Annealing Techniques, 34 Approximation Algorithms for NP-Hard Optimization Problems