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Sinopsis
This is a central topic in any computer science curriculum. To distinguish this textbook from others, the author considers probabilistic methods as being fundamental for the construction of simple and efficient algorithms, and in each chapter at least one problem is solved using a randomized algorithm. Data structures are discussed to the extent needed for the implementation of the algorithms. The specific algorithms examined were chosen because of their wide field of application.
This book originates from lectures for undergraduate and graduate students. The text assumes experience in programming algorithms, especially with elementary data structures such as chained lists, queues, and stacks. It also assumes familiarity with mathematical methods, although the author summarizes some basic notations and results from probability theory and related mathematical terminology in the appendices. He includes many examples to explain the individual steps of the algorithms, and he concludes each chapter with numerous exercises.
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Acerca del autor
Prof. Dr. Helmut Knebl is a researcher and lecturer in the Faculty of Informatics of the Technische Hochschule Nürnberg Georg Simon Ohm, where he has taught courses on the topic of this book to students of computer science, media, and business informatics at bachelor's and master's levels. He is the coauthor of the successful textbook Introduction to Cryptography, now in its 3rd edition.
De la contraportada
This is a central topic in any computer science curriculum. To distinguish this textbook from others, the author considers probabilistic methods as being fundamental for the construction of simple and efficient algorithms, and in each chapter at least one problem is solved using a randomized algorithm. Data structures are discussed to the extent needed for the implementation of the algorithms. The specific algorithms examined were chosen because of their wide field of application.
This book originates from lectures for undergraduate and graduate students. The text assumes experience in programming algorithms, especially with elementary data structures such as chained lists, queues, and stacks. It also assumes familiarity with mathematical methods, although the author summarizes some basic notations and results from probability theory and related mathematical terminology in the appendices. He includes many examples to explain the individual steps of the algorithms, and he concludes each chapter with numerous exercises.
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Algorithms and Data Structures : Foundations and Probabilistic Methods for Design and Analysis
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Springer International Publishing, 2020
ISBN 10: 3030597571
ISBN 13: 9783030597573
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Algorithms and Data Structures
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ISBN 10: 3030597571
ISBN 13: 9783030597573
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. A central topic in any computer science curriculumAuthor considers probabilistic methods as being fundamental for the construction of simple and efficient algorithmsSuitable for undergraduate and graduate students of computer science, mathe. Nº de ref. del artículo: 448685465
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Algorithms and Data Structures: Foundations and Probabilistic Methods for Design and Analysis
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Algorithms and Data Structures
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ISBN 10: 3030597571
ISBN 13: 9783030597573
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Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This is a central topic in any computer science curriculum. To distinguish this textbook from others, the author considers probabilistic methods as being fundamental for the construction of simple and efficient algorithms, and in each chapter at least one problem is solved using a randomized algorithm. Data structures are discussed to the extent needed for the implementation of the algorithms. The specific algorithms examined were chosen because of their wide field of application.This book originates from lectures for undergraduate and graduate students. The text assumes experience in programming algorithms, especially with elementary data structures such as chained lists, queues, and stacks. It also assumes familiarity with mathematical methods, although the author summarizes some basic notations and results from probability theory and related mathematical terminology in the appendices. He includes many examples to explain the individual steps of the algorithms, and he concludes each chapter with numerous exercises. 364 pp. Englisch. Nº de ref. del artículo: 9783030597573
Cantidad disponible: 2 disponibles
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Algorithms and Data Structures : Foundations and Probabilistic Methods for Design and Analysis
Publicado por
Springer International Publishing, 2020
ISBN 10: 3030597571
ISBN 13: 9783030597573
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Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This is a central topic in any computer science curriculum. To distinguish this textbook from others, the author considers probabilistic methods as being fundamental for the construction of simple and efficient algorithms, and in each chapter at least one problem is solved using a randomized algorithm. Data structures are discussed to the extent needed for the implementation of the algorithms. The specific algorithms examined were chosen because of their wide field of application.This book originates from lectures for undergraduate and graduate students. The text assumes experience in programming algorithms, especially with elementary data structures such as chained lists, queues, and stacks. It also assumes familiarity with mathematical methods, although the author summarizes some basic notations and results from probability theory and related mathematical terminology in the appendices. He includes many examples to explain the individual steps of the algorithms, and he concludes each chapter with numerous exercises. Nº de ref. del artículo: 9783030597573
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Algorithms and Data Structures: Foundations and Probabilistic Methods for Design and Analysis
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Algorithms and Data Structures : Foundations and Probabilistic Methods for Design and Analysis
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