Algorithms and Theory of Computation Handbook, Volume 1
General Concepts and Techniques
2nd Edition
Published on 20. November 2009
Book
Hardback
988 pages
978-1-58488-822-2 (ISBN)
Description
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 of the existing chapters, this second edition contains four new chapters that cover external memory and parameterized algorithms as well as computational number theory and algorithmic coding theory.
This best-selling handbook continues to help computer professionals and engineers find significant information on various algorithmic topics. The expert contributors clearly define the terminology, present basic results and techniques, and offer a number of current references to the in-depth literature. They also provide a glimpse of the major research issues concerning the relevant topics.
This best-selling handbook continues to help computer professionals and engineers find significant information on various algorithmic topics. The expert contributors clearly define the terminology, present basic results and techniques, and offer a number of current references to the in-depth literature. They also provide a glimpse of the major research issues concerning the relevant topics.
More details
Series
Edition
2nd edition
Language
English
Place of publication
Oxford
United States
Publishing group
Taylor & Francis Inc
Target group
Professional and scholarly
Professional
Edition type
New edition
Product notice
sewn/stitched
Cloth over boards
Illustrations
227 s/w Abbildungen, 22 s/w Tabellen
22 Tables, black and white; 227 Illustrations, black and white
Dimensions
Height: 261 mm
Width: 182 mm
Thickness: 50 mm
Weight
1905 gr
ISBN-13
978-1-58488-822-2 (9781584888222)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Mikhail J. Atallah | Marina Blanton
Algorithms and Theory of Computation Handbook, Volume 1
General Concepts and Techniques
Book
05/2017
2nd Edition
CRC Press
€115.60
Shipment within 10-20 days
Mikhail J. Atallah | Marina Blanton
Algorithms and Theory of Computation Handbook, Volume 1
General Concepts and Techniques
E-Book
11/2009
2nd Edition
Chapman & Hall/CRC
€109.99
Available for download
Mikhail J. Atallah | Marina Blanton
Algorithms and Theory of Computation Handbook, Volume 1
General Concepts and Techniques
E-Book
11/2009
2nd Edition
Chapman and Hall
€109.99
Available for download
Persons
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
Marina Blanton is an assistant professor in the computer science and engineering department at the University of Notre Dame
Content
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