Geometric Data Structures for Computer Graphics

Geometric Data Structures for Computer Graphics

Author: Elmar Langetepe

Publisher: A K Peters/CRC Press

Published: 2006

Total Pages: 344

ISBN-13:

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This book focuses on algorithms and geometric data structures that have proven to be versatile, efficient and fundamental. It endows practitioners in the computer graphics field with a working knowledge of a wide range of geometric data structures from computational geometry.


Computational Geometry

Computational Geometry

Author: Mark de Berg

Publisher: Springer Science & Business Media

Published: 2013-04-17

Total Pages: 370

ISBN-13: 3662042452

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This introduction to computational geometry focuses on algorithms. Motivation is provided from the application areas as all techniques are related to particular applications in robotics, graphics, CAD/CAM, and geographic information systems. Modern insights in computational geometry are used to provide solutions that are both efficient and easy to understand and implement.


Algorithms and Data Structures - Applications to Graphics and Geometry

Algorithms and Data Structures - Applications to Graphics and Geometry

Author: Textbook Equity

Publisher: Lulu.com

Published: 2014-09-15

Total Pages: 371

ISBN-13: 1312512938

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This is a college-level introductory textbook of algorithms and data structures with application to graphics and geometry. This textbook, released under a Creative Commons Share Alike (CC BY SA) license, is presented in its original format with the academic content unchanged. It was authored by Jurg Nievergelt (ETH Zurich) and Klaus Hinrichs (Institut fur Informatik) and provided by the University of Georgia's Global Textbook Project. Textbookequity.org/algorithms-and-data-structures/ Photo Credit: Renato Keshet (GFDL) commons.wikimedia.org Contents Part I: Programming environments for motion, graphics, and geometry Part II: Programming concepts: beyond notation Part IV: Complexity of problems and algorithms Part V: Data structures Textbook Equity Edition http: //textbookequity.org/algorithms-and-data-structures


Algorithms and Data Structures

Algorithms and Data Structures

Author: Jurg Nievergelt

Publisher:

Published: 2011

Total Pages:

ISBN-13:

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"This is a textbook for first year Computer Science. Algorithms and Data Structures With Applications to Graphics and Geometry."--BC Campus website.


Algorithms and Data Structures

Algorithms and Data Structures

Author: Kurt Mehlhorn

Publisher: Springer Science & Business Media

Published: 2008-05-27

Total Pages: 300

ISBN-13: 3540779787

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Algorithms are at the heart of every nontrivial computer application, and algorithmics is a modern and active area of computer science. Every computer scientist and every professional programmer should know about the basic algorithmic toolbox: structures that allow efficient organization and retrieval of data, frequently used algorithms, and basic techniques for modeling, understanding and solving algorithmic problems. This book is a concise introduction addressed to students and professionals familiar with programming and basic mathematical language. Individual chapters cover arrays and linked lists, hash tables and associative arrays, sorting and selection, priority queues, sorted sequences, graph representation, graph traversal, shortest paths, minimum spanning trees, and optimization. The algorithms are presented in a modern way, with explicitly formulated invariants, and comment on recent trends such as algorithm engineering, memory hierarchies, algorithm libraries and certifying algorithms. The authors use pictures, words and high-level pseudocode to explain the algorithms, and then they present more detail on efficient implementations using real programming languages like C++ and Java. The authors have extensive experience teaching these subjects to undergraduates and graduates, and they offer a clear presentation, with examples, pictures, informal explanations, exercises, and some linkage to the real world. Most chapters have the same basic structure: a motivation for the problem, comments on the most important applications, and then simple solutions presented as informally as possible and as formally as necessary. For the more advanced issues, this approach leads to a more mathematical treatment, including some theorems and proofs. Finally, each chapter concludes with a section on further findings, providing views on the state of research, generalizations and advanced solutions.


A Practical Introduction to Data Structures and Algorithm Analysis

A Practical Introduction to Data Structures and Algorithm Analysis

Author: Clifford A. Shaffer

Publisher:

Published: 2001

Total Pages: 536

ISBN-13:

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This practical text contains fairly "traditional" coverage of data structures with a clear and complete use of algorithm analysis, and some emphasis on file processing techniques as relevant to modern programmers. It fully integrates OO programming with these topics, as part of the detailed presentation of OO programming itself.Chapter topics include lists, stacks, and queues; binary and general trees; graphs; file processing and external sorting; searching; indexing; and limits to computation.For programmers who need a good reference on data structures.


Think Data Structures

Think Data Structures

Author: Allen B. Downey

Publisher: "O'Reilly Media, Inc."

Published: 2017-07-07

Total Pages: 149

ISBN-13: 1491972319

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If you’re a student studying computer science or a software developer preparing for technical interviews, this practical book will help you learn and review some of the most important ideas in software engineering—data structures and algorithms—in a way that’s clearer, more concise, and more engaging than other materials. By emphasizing practical knowledge and skills over theory, author Allen Downey shows you how to use data structures to implement efficient algorithms, and then analyze and measure their performance. You’ll explore the important classes in the Java collections framework (JCF), how they’re implemented, and how they’re expected to perform. Each chapter presents hands-on exercises supported by test code online. Use data structures such as lists and maps, and understand how they work Build an application that reads Wikipedia pages, parses the contents, and navigates the resulting data tree Analyze code to predict how fast it will run and how much memory it will require Write classes that implement the Map interface, using a hash table and binary search tree Build a simple web search engine with a crawler, an indexer that stores web page contents, and a retriever that returns user query results Other books by Allen Downey include Think Java, Think Python, Think Stats, and Think Bayes.