Geometric Algebra Computing
in Engineering and Computer Science
Editors: Bayro Corrochano, Eduardo, Scheuermann, Gerik (Eds.)
 Presents novel, pioneering research on the study and applications of Clifford (geometric) algebra
 Diverse areas of application are discussed, including neural computing and learning, robotics and computer vision, image processing, colour and scene analysis
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 About this book

Geometric algebra provides a rich and general mathematical framework for the development of solutions, concepts and computer algorithms without losing geometric insight into the problem in question. Many current mathematical subjects can be treated in an unified manner without abandoning the mathematical system of geometric algebra, such as multilinear algebra, projective and affine geometry, calculus on manifolds, Riemann geometry, the representation of Lie algebras and Lie groups using bivector algebras, and conformal geometry.
Geometric Algebra Computing in Engineering and Computer Science presents contributions from an international selection of experts in the field. This useful text/reference offers new insights and solutions for the development of theorems, algorithms and advanced methods for realtime applications across a range of disciplines. The book also provides an introduction to advanced screw theory and conformal geometry. Written in an accessible style, the discussion of all applications is enhanced by the inclusion of numerous examples, figures and experimental analysis.
Topics and features:
 Provides a thorough discussion of several tasks for image processing, pattern recognition, computer vision, robotics and computer graphics using the geometric algebra framework
 Introduces nonspecialists to screw theory in the geometric algebra framework, offering a tutorial on conformal geometric algebra and an overview of recent applications of geometric algebra
 Explores new developments in the domain of Clifford Fourier Transforms and Clifford Wavelet Transform, including novel applications of Clifford Fourier transforms for 3D visualization and colour image spectral analysis
 Presents a detailed study of fluid flow problems with quaternionic analysis
 Examines new algorithms for geometric neural computing and cognitive systems
 Analyzes computer software packages for extensive calculations in geometric algebra, investigating the algorithmic complexity of key geometric operations and how the program code can be optimized for realtime computations
The book is an essential resource for computer scientists, applied physicists, AI researchers and mechanical and electrical engineers. It will also be of value to graduate students and researchers interested in a modern language for geometric computing.
Prof. Dr. Eng. Eduardo BayroCorrochano is a Full Professor of Geometric Computing at Cinvestav, Mexico. He is the author of the Springer titles Geometric Computing for Perception Action Systems, Handbook of Geometric Computing, and Geometric Computing for Wavelet Transforms, Robot Vision, Learning, Control and Action.
Prof. Dr. Gerik Scheuermann is a Full Professor at the University of Leipzig, Germany. He is the author of the Springer title TopologyBased Methods in Visualization II.
 Reviews

From the reviews:
“This book is a result of the edited proceedings of the 2008 conference. It contains many advanced ideas from mathematics, physics, and computer science, and … serve as a reference book on geometric algebra and its applications. … includes numerous color illustrations, and the chapters end with references to the literature. … This book should be treasured for presenting various geometric algebra applications in several areas … . It will be useful to physicists, computer scientists, and engineers. … this is a very useful book.” (S. V. Nagaraj, ACM Computing Reviews, February, 2012)
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Bibliographic Information
 Bibliographic Information

 Book Title
 Geometric Algebra Computing
 Book Subtitle
 in Engineering and Computer Science
 Editors

 Eduardo Bayro Corrochano
 Gerik Scheuermann
 Copyright
 2010
 Publisher
 SpringerVerlag London
 Copyright Holder
 SpringerVerlag London Limited
 eBook ISBN
 9781849961080
 DOI
 10.1007/9781849961080
 Hardcover ISBN
 9781849961073
 Softcover ISBN
 9781447157687
 Edition Number
 1