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Cover: 9783031170454 | Problems on Algorithms | Habib Izadkhah | Taschenbuch | xii | Englisch
Rückseite: 9783031170454 | Problems on Algorithms | Habib Izadkhah | Taschenbuch | xii | Englisch
Cover: 9783031170454 | Problems on Algorithms | Habib Izadkhah | Taschenbuch | xii | Englisch
Rückseite: 9783031170454 | Problems on Algorithms | Habib Izadkhah | Taschenbuch | xii | Englisch
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Problems on Algorithms
A Comprehensive Exercise Book for Students in Software Engineering
Taschenbuch von Habib Izadkhah
Sprache: Englisch

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Beschreibung
With approximately 2500 problems, this book provides a collection of practical problems on the basic and advanced data structures, design, and analysis of algorithms. To make this book suitable for self-instruction, about one-third of the algorithms are supported by solutions, and some others are supported by hints and comments. This book is intended for students wishing to deepen their knowledge of algorithm design in an undergraduate or beginning graduate class on algorithms, for those teaching courses in this area, for use by practicing programmers who wish to hone and expand their skills, and as a self-study text for graduate students who are preparing for the qualifying examination on algorithms for a Ph.D. program in Computer Science or Computer Engineering. About all, it is a good source for exam problems for those who teach algorithms and data structure. The format of each chapter is just a little bit of instruction followed by lots of problems.
This book is intended to augment the problem sets found in any standard algorithms textbook.
This book
¿ begins with four chapters on background material that most algorithms instructors would like their students to have mastered before setting foot in an algorithms class. The introductory chapters include mathematical induction, complexity notations, recurrence relations, and basic algorithm analysis methods.
¿ provides many problems on basic and advanced data structures including basic data structures (arrays, stack, queue, and linked list), hash, tree, search, and sorting algorithms.
¿ provides many problems on algorithm design techniques: divide and conquer, dynamic programming, greedy algorithms, graph algorithms, and backtracking algorithms.
¿ is rounded out with a chapter on NP-completeness.
With approximately 2500 problems, this book provides a collection of practical problems on the basic and advanced data structures, design, and analysis of algorithms. To make this book suitable for self-instruction, about one-third of the algorithms are supported by solutions, and some others are supported by hints and comments. This book is intended for students wishing to deepen their knowledge of algorithm design in an undergraduate or beginning graduate class on algorithms, for those teaching courses in this area, for use by practicing programmers who wish to hone and expand their skills, and as a self-study text for graduate students who are preparing for the qualifying examination on algorithms for a Ph.D. program in Computer Science or Computer Engineering. About all, it is a good source for exam problems for those who teach algorithms and data structure. The format of each chapter is just a little bit of instruction followed by lots of problems.
This book is intended to augment the problem sets found in any standard algorithms textbook.
This book
¿ begins with four chapters on background material that most algorithms instructors would like their students to have mastered before setting foot in an algorithms class. The introductory chapters include mathematical induction, complexity notations, recurrence relations, and basic algorithm analysis methods.
¿ provides many problems on basic and advanced data structures including basic data structures (arrays, stack, queue, and linked list), hash, tree, search, and sorting algorithms.
¿ provides many problems on algorithm design techniques: divide and conquer, dynamic programming, greedy algorithms, graph algorithms, and backtracking algorithms.
¿ is rounded out with a chapter on NP-completeness.
Über den Autor
Dr. Habib Izadkhah is an associate professor at the Department of Computer Science, University of Tabriz, Iran. He worked in the industry for a decade as a software engineer before becoming an academic. His research interests include algorithms and graphs, software engineering, and bioinformatics. More recently, he has been working on developing and applying deep learning to a variety of problems, dealing with biomedical images, speech recognition, text understanding, and generative models. He has contributed to various research projects, authored a number of research papers in international conferences, workshops, and journals, and also has written five books, including Source Code Modularization: Theory and Techniques from Springer and Deep Learning in Bioinformatics from Elsevier.
Inhaltsverzeichnis
Mathematical Induction.- Growth of Functions.- Recurrence Relations.- Algorithm Analysis.- Basic Data Structure.- Hash.- Tree.- Search.- Sorting.- Divide and Conquer.- Dynamic Programming.- Greedy Algorithms.- Graph.- Backtracking Algorithms.- P, NP, NP-Complete, and NP-Hard Problems.
Details
Erscheinungsjahr: 2023
Fachbereich: Technik allgemein
Genre: Mathematik, Medizin, Naturwissenschaften, Technik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Inhalt: xii
513 S.
91 s/w Illustr.
4 farbige Illustr.
513 p. 95 illus.
4 illus. in color.
ISBN-13: 9783031170454
ISBN-10: 3031170458
Sprache: Englisch
Einband: Kartoniert / Broschiert
Autor: Izadkhah, Habib
Auflage: 1st edition 2022
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 29 mm
Von/Mit: Habib Izadkhah
Erscheinungsdatum: 03.11.2023
Gewicht: 0,791 kg
Artikel-ID: 127803647
Über den Autor
Dr. Habib Izadkhah is an associate professor at the Department of Computer Science, University of Tabriz, Iran. He worked in the industry for a decade as a software engineer before becoming an academic. His research interests include algorithms and graphs, software engineering, and bioinformatics. More recently, he has been working on developing and applying deep learning to a variety of problems, dealing with biomedical images, speech recognition, text understanding, and generative models. He has contributed to various research projects, authored a number of research papers in international conferences, workshops, and journals, and also has written five books, including Source Code Modularization: Theory and Techniques from Springer and Deep Learning in Bioinformatics from Elsevier.
Inhaltsverzeichnis
Mathematical Induction.- Growth of Functions.- Recurrence Relations.- Algorithm Analysis.- Basic Data Structure.- Hash.- Tree.- Search.- Sorting.- Divide and Conquer.- Dynamic Programming.- Greedy Algorithms.- Graph.- Backtracking Algorithms.- P, NP, NP-Complete, and NP-Hard Problems.
Details
Erscheinungsjahr: 2023
Fachbereich: Technik allgemein
Genre: Mathematik, Medizin, Naturwissenschaften, Technik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Inhalt: xii
513 S.
91 s/w Illustr.
4 farbige Illustr.
513 p. 95 illus.
4 illus. in color.
ISBN-13: 9783031170454
ISBN-10: 3031170458
Sprache: Englisch
Einband: Kartoniert / Broschiert
Autor: Izadkhah, Habib
Auflage: 1st edition 2022
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 29 mm
Von/Mit: Habib Izadkhah
Erscheinungsdatum: 03.11.2023
Gewicht: 0,791 kg
Artikel-ID: 127803647
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