Practical Analysis of Algorithms
- 9h 43m
- Dana Vrajitoru, William Knight
- Springer
- 2014
This book introduces the essential concepts of algorithm analysis required by core undergraduate and graduate computer science courses, in addition to providing a review of the fundamental mathematical notions necessary to understand these concepts. Features: includes numerous fully-worked examples and step-by-step proofs, assuming no strong mathematical background; describes the foundation of the analysis of algorithms theory in terms of the big-Oh, Omega, and Theta notations; examines recurrence relations; discusses the concepts of basic operation, traditional loop counting, and best case and worst case complexities; reviews various algorithms of a probabilistic nature, and uses elements of probability theory to compute the average complexity of algorithms such as Quicksort; introduces a variety of classical finite graph algorithms, together with an analysis of their complexity; provides an appendix on probability theory, reviewing the major definitions and theorems used in the book.
In this Book
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Introduction
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Mathematical Preliminaries
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Fundamental Notations in Analysis of Algorithms
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Recurrence Relations
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Deterministic Analysis of Algorithms
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Algorithms and Probabilities
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Finite Graph Algorithms
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Appendix—Probability Theory
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References
