Introduction to the Design and Analysis of Algorithms / Edition 1by Anany V. Levitin
Pub. Date: 10/30/2002
Publisher: Addison Wesley
Based on a new classification of algorithm design techniques and a clear delineation of analysis methods, Introduction to the Design and Analysis of Algorithms presents the subject in a truly innovative manner. Written in a reader-friendly style, the book encourages broad problem-solving skills while thoroughly covering the material required for/i>
Based on a new classification of algorithm design techniques and a clear delineation of analysis methods, Introduction to the Design and Analysis of Algorithms presents the subject in a truly innovative manner. Written in a reader-friendly style, the book encourages broad problem-solving skills while thoroughly covering the material required for introductory algorithms. The author emphasizes conceptual understanding before the introduction of the formal treatment of each technique. Popular puzzles are used to motivate readers' interest and strengthen their skills in algorithmic problem solving. Other enhancement features include chapter summaries, hints to the exercises, and a solution manual. For those interested in learning more about algorithms.
- Addison Wesley
- Publication date:
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- Older Edition
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- 7.30(w) x 9.20(h) x 1.20(d)
Table of Contents(Each chapter ends with a “Summary”.)
The notion of algorithm.
Fundamentals of algorithmic problem solving.
Important problem types.
Fundamental data structures.
2. Fundamentals of the Analysis of Algorithm Efficiency.
Asymptotic notations and standard efficiency classes.
Mathematical analysis of nonrecursive algorithms.
Mathematical analysis of recursive algorithms.
Example: Fibonacci numbers.
Empirical analysis of algorithms.
3. Brute Force.
Selection sort and bubble sort.
Sequential search and brute-force string matching.
The closest-pair and convex-hull problems by brute force.
Binary tree traversals and related properties.
Multiplication of large integers and Strassen's matrix multiplication.
Closest-pair and convex-hull problems by divide-and-conquer.
Depth-first search and breadth-first search.
Algorithms for generating combinatorial objects.
Balanced search trees.
Heaps and heapsort.
Horner's rule and binaryexponentiation.
7. Space and Time Tradeoffs.
Sorting by counting.
Horspool's and Boyer-Moore algorithms for string matching.
8. Dynamic Programming.
Computing a binomial coefficient.
Warshall's and Floyd's algorithms.
Optimal binary search trees.
The knapsack problem and memory functions.
9. Greedy Technique.
10. Limitations of Algorithm Power.
P, NP, and NP-complete problems.
Challenges of numerical algorithms.
11. Coping with the Limitations of Algorithm Power.
Approximation algorithms for NP-hard problems.
Algorithms for solving nonlinear equations.
Appendix A: Useful Formulas for the Analysis of Algorithms.
Appendix B: Short Tutorial on Recurrence Relations.
Hints to Exercises.
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