Algorithms and Data Structures: Foundations and Probabilistic Methods for Design and Analysis Paperback - 2021
by Helmut Knebl
- New
- Paperback
- first
A$220.66
A$21.64
Delivery to USA
Standard delivery: 20 to 30 days
More delivery options
Standard delivery: 20 to 30 days
Ships from Sanctum Books (Delhi, India)
Details
- Title Algorithms and Data Structures: Foundations and Probabilistic Methods for Design and Analysis
- Author Helmut Knebl
- Binding Paperback
- Edition 1
- Condition New
- Pages 349
- Volumes 1
- Language ENG
- Publisher Springer
- Publication date 2021
- Illustrated Yes
- Features Illustrated
- Bookseller's Inventory # Atlantic-9783030597603
- ISBN 9783030597603 / 3030597601
- Weight 1.12 lbs (0.51 kg)
- Dimensions 9.21 x 6.14 x 0.75 in (23.39 x 15.60 x 1.91 cm)
- Category Computers - Languages / Programming
- Quantity available 500
About Sanctum Books Delhi, India
Specialising in: Art, Archaeology, Art History, And Architecture, Dictionaries And Encyclopaedias, Indian History, Languages, Literature, And Linguistics, Music, Dance, Theatre, And Cinema, Numismatics, Philately, And Epigraphy, Philosophy & Philosophy Of Science, Religion (Buddhism, Jainism, Hinduism, Sikhism, And Islam)
Biblio member since 2010
We are leading publishers, booksellers, distributors, importers, and exporters. We carry a large selection of books on varied subjects. Do place your valued order or let us know your requirement via email.
30 day return guarantee, with full refund including shipping costs for up to 30 days after delivery if an item arrives misdescribed or damaged.
�
Books are shipped by Registered Air Mail or DHL/FedEx/Aramex. Additional shipping charges may be required for multi-volume sets.
Reader reviews for Algorithms and Data Structures: Foundations and Probabilistic Methods for Design and Analysis
Write a review for this book
Important Terms and Guidelines
- Please focus on the book’s content and context. Also, add any personal comments as to how you enjoyed the book. Substantiate your likes and dislikes. You may make comparisons to other books.
- Reviews must be at least 140 characters in length.
- Please do not reveal critical plot elements.
- This is not a help line. Contact customer support if you need help.
Your review must not include:
- Obscenities, discriminatory language, or other insulting language not suitable for public domain
- Advertisements, “spam” content, or references to other products, offers or websites.
- Email addresses, URLs, phone numbers, physical addresses or other contact information.
- Overly critical comments about other reviews or reviewers
- Time-sensitive material (i.e. promotional tours, seminars, lectures, etc.)
- Availability, price, or alternative ordering/shipping information
From the rear cover
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 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.