Practical Analysis of Algorithms (Undergraduate Topics in Computer Science)

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9783319098876: Practical Analysis of Algorithms (Undergraduate Topics in Computer Science)
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“The book is dedicated to an old, important and complex topic in computer science. … The multiple exercises in each section invite the readers to a deeper exploration of the subjects. The formalized style of the book is expected to attract especially young students introduced already to mathematical formalisms. The material can be used as a textbook for undergraduate courses in computer science.” (Dana Petcu, zbMATH, Vol. 1303, 2015)

Vom Verlag:

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.

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Vrajitoru, Dana; Knight, William
Verlag: Springer-Verlag Gmbh Okt 2014 (2014)
ISBN 10: 331909887X ISBN 13: 9783319098876
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Buchbeschreibung Springer-Verlag Gmbh Okt 2014, 2014. Taschenbuch. Buchzustand: Neu. 23.5x15.5x cm. Neuware - 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. 466 pp. Englisch. Artikel-Nr. 9783319098876

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