Fundamentals of Algorithmics
International Edition
Pearson (Publisher)
Published on 6. September 1995
Book
Paperback/Softback
524 pages
978-0-13-073487-7 (ISBN)
Description
This is an introductory-level algorithm text. It includes worked-out examples and detailed proofs. Presents Algorithms by type rather than application.* structures material by techniques employed, not by the application area, so students can progress from the underlying abstract concepts to the concrete application essentials. * begins with a compact, but complete introduction to some necessary math, and also includes a long introduction to proofs by contradiction and mathematical induction. This serves to fill the gaps that many undergraduates have in their mathematical knowledge. * gives a paced, thorough introduction to the analysis of algorithms, and uses coherent notation and unusually detailed treatment of solving recurrences. * includes a chapter on probabilistic algorithms, and an introduction to parallel algorithms, both of which are becoming increasingly important. * approaches the analysis and design of algorithms by type rather than by application.
More details
Language
English
Place of publication
United States
Publishing group
Pearson Education (US)
Target group
Professional and scholarly
Dimensions
Height: 240 mm
Width: 177 mm
Thickness: 20 mm
Weight
755 gr
ISBN-13
978-0-13-073487-7 (9780130734877)
Copyright in bibliographic data is held by Nielsen Book Services Limited or its licensors: all rights reserved.
Schweitzer Classification
Other editions
Previous edition

Book
12/1995
Pearson
€188.16
Article exhausted; check for reprint
Content
1. Preliminaries.
2. Elementary Algorithmicss.
3. Asymptotic Notation.
4. Analysis of Algorithms.
5. Some Data Structures.
6. Greedy Algorithms.
7. Divide-And-Conquer.
8. Dynamic Programming.
9. Exploring Graphs.
10. Probabilistic Algorithms.
11. Parallel Algorithms.
12. Computational Complexity.
13. Heuristic and Approximate Algorithms.
References.
Index.
2. Elementary Algorithmicss.
3. Asymptotic Notation.
4. Analysis of Algorithms.
5. Some Data Structures.
6. Greedy Algorithms.
7. Divide-And-Conquer.
8. Dynamic Programming.
9. Exploring Graphs.
10. Probabilistic Algorithms.
11. Parallel Algorithms.
12. Computational Complexity.
13. Heuristic and Approximate Algorithms.
References.
Index.