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Sprache:
Englisch
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Beschreibung
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.
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.
Über den 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.
Zusammenfassung
A central topic in any computer science curriculum
Author considers probabilistic methods as being fundamental for the construction of simple and e?cient algorithms
Suitable for undergraduate and graduate students of computer science, mathematics, and engineering
Inhaltsverzeichnis
Introduction.- Sorting and Searching.- Hashing.- Trees.- Graphs.- Weighted Graphs.- App. A, Probabilities.- App. B, Mathematical Terminology and Useful Formulas.- References.- Symbols.- Index.
Details
| Erscheinungsjahr: | 2021 |
|---|---|
| Genre: | Informatik, Mathematik, Medizin, Naturwissenschaften, Technik |
| Rubrik: | Naturwissenschaften & Technik |
| Medium: | Taschenbuch |
| Inhalt: |
xi
349 S. |
| ISBN-13: | 9783030597603 |
| ISBN-10: | 3030597601 |
| Sprache: | Englisch |
| Einband: | Kartoniert / Broschiert |
| Autor: | Knebl, Helmut |
| Auflage: | 1st edition 2020 |
| Hersteller: | Springer International Publishing |
| Verantwortliche Person für die EU: | Springer Verlag GmbH, Tiergartenstr. 17, D-69121 Heidelberg, juergen.hartmann@springer.com |
| Maße: | 235 x 155 x 20 mm |
| Von/Mit: | Helmut Knebl |
| Erscheinungsdatum: | 02.11.2021 |
| Gewicht: | 0,552 kg |
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