Computational Geometry: Methods and Applications
by Jianer Chen
Number of pages: 227
In this book, we concentrate on four major directions in computational geometry: the construction of convex hulls, proximity problems, searching problems and intersection problems. Computational geometry is of practical importance because Euclidean space of two and three dimensions forms the arena in which real physical objects are arranged. A large number of applications areas such as pattern recognition, computer graphics, image processing, operations research, statistics, computer-aided design, robotics, etc., have been the incubation bed of the discipline since they provide inherently geo metric problems for which efficient algorithms have to be developed. A large number of manufacturing problems involve wire layout, facilities location, cutting-stock and related geometric optimization problems. Solving these efficiently on a high-speed computer requires the development of new geo metrical tools, as well as the application of fast-algorithm techniques, and is not simply a matter of translating well-known theorems into computer programs. From a theoretical standpoint, the complexity of geometric algo rithms is of interest because it sheds new light on the intrinsic difficulty of computation.
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A data structure is a particular way of storing and organizing data in a computer so that it can be used efficiently. Contents of the book: Sequences; Dictionaries; Sets; Priority queues; Successors and neighbors; Integer and string searching.
by Granville Barnett, Luca Del Tongo - DotNetSlackers
The book provides implementations of common and uncommon algorithms in pseudocode which is language independent and provides for easy porting to most programming languages. We assume that the reader is familiar with the object oriented concepts.
by Robert Sedgewick, Kevin Wayne - Addison-Wesley Professional
This textbook surveys the most important algorithms and data structures in use today. Applications to science, engineering, and industry are a key feature of the text. We motivate each algorithm by examining its impact on specific applications.
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The book is useful for scientists who gather data and seek tools for analyzing and interpreting data. It will be a reference for scientists in a variety of disciplines and can serve as a textbook for a graduate course in exploratory data analysis.