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Titlebook: Geometric Algebra Computing; in Engineering and C Eduardo Bayro-Corrochano,Gerik Scheuermann Book 2010 Springer-Verlag London Limited 2010

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書(shū)目名稱(chēng)Geometric Algebra Computing
副標(biāo)題in Engineering and C
編輯Eduardo Bayro-Corrochano,Gerik Scheuermann
視頻videohttp://file.papertrans.cn/384/383439/383439.mp4
概述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 comp
圖書(shū)封面Titlebook: Geometric Algebra Computing; in Engineering and C Eduardo Bayro-Corrochano,Gerik Scheuermann Book 2010 Springer-Verlag London Limited 2010
描述.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 real-time 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 proces
出版日期Book 2010
關(guān)鍵詞3D graphics; algebra; algorithms; calibration; computer vision; construction; geometry; graphics; holography
版次1
doihttps://doi.org/10.1007/978-1-84996-108-0
isbn_softcover978-1-4471-5768-7
isbn_ebook978-1-84996-108-0
copyrightSpringer-Verlag London Limited 2010
The information of publication is updating

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Engineering Graphics in Geometric Algebraing applications. A?number of example applications are reviewed. Geometric algebra unites many underpinning mathematical concepts in computer graphics such as vector algebra and vector fields, quaternions, kinematics and projective geometry, and it easily deals with geometric objects, operations, an
地板
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Parameterization of 3D Conformal Transformations in Conformal Geometric Algebraations. By providing a 5D algebraic representation of 3D geometric configurations, conformal geometric algebra proves to be very helpful in pose estimation, motion design, and neuron-based machine learning (Bayro-Corrochano et al., J.?Math. Imaging Vis. 24(1):55–81, .; Dorst et al., Geometric Algebr
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Analyzing Real Vector Fields with Clifford Convolution and Clifford–Fourier Transformds. While image processing of scalar data is a well-established discipline, there is a lack of similar methods for vector data. This paper surveys a particular approach defining convolution operators on vector fields using geometric algebra. This includes a corresponding Clifford–Fourier transform i
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發(fā)表于 2025-3-22 21:53:12 | 只看該作者
Clifford–Fourier Transform for Color Image Processingefine such a transformation using quaternions or Clifford algebras. We focus here on a geometric approach using group actions. The idea is to generalize the usual definition based on the characters of abelian groups by considering group morphisms from ?. to spinor groups Spin(3) and Spin(4). The tra
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Hilbert Transforms in Clifford Analysised to extract global and instantaneous characteristics, such as frequency, amplitude, and phase, from real signals. The multidimensional approach to the Hilbert transform usually is a tensorial one, considering the so-called Riesz transforms in each of the cartesian variables separately. In this pap
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Geometric Neural Computing for 2D Contour and 3D Surface Reconstructiontworks. Our approach is based on the self-organized neural network called Growing Neural Gas (GNG), incorporating versors of the geometric algebra in its neural units; such versors are the transformations that will be determined during the training stage and then applied to a point to approximate th
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