Algorithms - 04 edition
Algorithms - 04 edition
ISBN13: 9780023606922
ISBN10: 0023606924
by Richard Johnsonbaugh and Marcus Schaefer
Cover type: HardbackEdition: 04
Copyright: 2004
Publisher: Prentice Hall, Inc.
Published: 2004
International: No
ISBN13: 9780023606922
ISBN10: 0023606924
List price: $196.50
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Summary
For upper-level undergraduate and graduate courses in algorithms.
Filling the void left by other algorithms books, Algorithms and Data Structures provides an approach that emphasizes design techniques. The text includes application of algorithms, examples, end-of-section exercises, end-of-chapter exercises, hints and solutions to selected exercises, figures and notes to help the reader master the design and analysis of algorithms.
Features
- Numerous algorithm traces throughout the book.
- Enables students to check their understanding of the algorithm.
- Over 1,000 end-of-section exercises--With answers to 1/3 of them in the back of the book.
- Helps students practice solving problems.
- More applications than other algorithms texts.
- Provides students with applications to computer science to motivate the material.
- Elaborate world wide web site--With up-to-date support for book. An icon occurs throughout the book to indicate more explanations and examples available on the web.
- Provides students with expanded explanations of particular topics and additional information on algorithms.
- Upper bounds for worst-case times proven sharp.
- Provides students with proved sharp bounds.
- Lower bounds integrated into sections that discuss problems--e.g. after presentation of several sorting algorithms, text discusses lower bound for comparison-based sorting.
- Provides students with easy to follow organization.
- Methods used to solve NP-complete problems--Including approximation, brute force, parameterized complexity, and heuristics.
- Provides students with comprehensive chapter on topics with significant importance in algorithms.
- Recent results--Such as Pearson's polynomial-time algorithm for the coin-changing problem and parameterized complexity.
- Provides students with up-to-date presentation that helps motivate the material.
- Figures and tables illustrate concepts--Figure captions provide additional explanations and insight.
- Shows students how algorithms work to elucidate proofs.
Table of Contents
1. Mathematical Prerequisites.
2. Data Structures.
3. Searching Techniques.
4. Divide-and-Conquer.
5. Sorting and Selection.
6. Greedy Algorithms.
7. Dynamic Programming.
8. Text Searching.
9. Computational Algebra.
10. P and NP.
11. Coping with NP-Completeness.
12. Parallel Algorithms.
References.
Solutions to Selected Exercises.
Index.
shop us with confidence
For upper-level undergraduate and graduate courses in algorithms.
Filling the void left by other algorithms books, Algorithms and Data Structures provides an approach that emphasizes design techniques. The text includes application of algorithms, examples, end-of-section exercises, end-of-chapter exercises, hints and solutions to selected exercises, figures and notes to help the reader master the design and analysis of algorithms.
Features
- Numerous algorithm traces throughout the book.
- Enables students to check their understanding of the algorithm.
- Over 1,000 end-of-section exercises--With answers to 1/3 of them in the back of the book.
- Helps students practice solving problems.
- More applications than other algorithms texts.
- Provides students with applications to computer science to motivate the material.
- Elaborate world wide web site--With up-to-date support for book. An icon occurs throughout the book to indicate more explanations and examples available on the web.
- Provides students with expanded explanations of particular topics and additional information on algorithms.
- Upper bounds for worst-case times proven sharp.
- Provides students with proved sharp bounds.
- Lower bounds integrated into sections that discuss problems--e.g. after presentation of several sorting algorithms, text discusses lower bound for comparison-based sorting.
- Provides students with easy to follow organization.
- Methods used to solve NP-complete problems--Including approximation, brute force, parameterized complexity, and heuristics.
- Provides students with comprehensive chapter on topics with significant importance in algorithms.
- Recent results--Such as Pearson's polynomial-time algorithm for the coin-changing problem and parameterized complexity.
- Provides students with up-to-date presentation that helps motivate the material.
- Figures and tables illustrate concepts--Figure captions provide additional explanations and insight.
- Shows students how algorithms work to elucidate proofs.
1. Mathematical Prerequisites.
2. Data Structures.
3. Searching Techniques.
4. Divide-and-Conquer.
5. Sorting and Selection.
6. Greedy Algorithms.
7. Dynamic Programming.
8. Text Searching.
9. Computational Algebra.
10. P and NP.
11. Coping with NP-Completeness.
12. Parallel Algorithms.
References.
Solutions to Selected Exercises.
Index.
Published: 2004
International: No
Summary
For upper-level undergraduate and graduate courses in algorithms.
Filling the void left by other algorithms books, Algorithms and Data Structures provides an approach that emphasizes design techniques. The text includes application of algorithms, examples, end-of-section exercises, end-of-chapter exercises, hints and solutions to selected exercises, figures and notes to help the reader master the design and analysis of algorithms.
Features
- Numerous algorithm traces throughout the book.
- Enables students to check their understanding of the algorithm.
- Over 1,000 end-of-section exercises--With answers to 1/3 of them in the back of the book.
- Helps students practice solving problems.
- More applications than other algorithms texts.
- Provides students with applications to computer science to motivate the material.
- Elaborate world wide web site--With up-to-date support for book. An icon occurs throughout the book to indicate more explanations and examples available on the web.
- Provides students with expanded explanations of particular topics and additional information on algorithms.
- Upper bounds for worst-case times proven sharp.
- Provides students with proved sharp bounds.
- Lower bounds integrated into sections that discuss problems--e.g. after presentation of several sorting algorithms, text discusses lower bound for comparison-based sorting.
- Provides students with easy to follow organization.
- Methods used to solve NP-complete problems--Including approximation, brute force, parameterized complexity, and heuristics.
- Provides students with comprehensive chapter on topics with significant importance in algorithms.
- Recent results--Such as Pearson's polynomial-time algorithm for the coin-changing problem and parameterized complexity.
- Provides students with up-to-date presentation that helps motivate the material.
- Figures and tables illustrate concepts--Figure captions provide additional explanations and insight.
- Shows students how algorithms work to elucidate proofs.
Table of Contents
Table of Contents
1. Mathematical Prerequisites.
2. Data Structures.
3. Searching Techniques.
4. Divide-and-Conquer.
5. Sorting and Selection.
6. Greedy Algorithms.
7. Dynamic Programming.
8. Text Searching.
9. Computational Algebra.
10. P and NP.
11. Coping with NP-Completeness.
12. Parallel Algorithms.
References.
Solutions to Selected Exercises.
Index.
