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Titlebook: Systems, Patterns and Data Engineering with Geometric Calculi; Sebastià Xambó-Descamps Conference proceedings 2021 The Editor(s) (if appli

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书目名称Systems, Patterns and Data Engineering with Geometric Calculi
编辑Sebastià Xambó-Descamps
视频video
概述Integrated perspective of mathematical engineering based on geometric calculi.A comprehensive formalism for deep neural networks based on geometric algebras.Coverage of relevant algorithms, particular
丛书名称SEMA SIMAI Springer Series
图书封面Titlebook: Systems, Patterns and Data Engineering with Geometric Calculi;  Sebastià Xambó-Descamps Conference proceedings 2021 The Editor(s) (if appli
描述.The intention of this collection agrees with the purposes of the homonymous mini-symposium (MS) at ICIAM-2019, which were to overview the essentials of geometric calculus (GC) formalism, to report on state-of-the-art applications showcasing its advantages and to explore the bearing of GC in novel approaches to deep learning. The first three contributions, which correspond to lectures at the MS, offer perspectives on recent advances in the application GC in the areas of robotics, molecular geometry, and medical imaging. The next three, especially invited, hone the expressiveness of GC in orientation measurements under different metrics, the treatment of contact elements, and the investigation of efficient computational methodologies. The last two, which also correspond to lectures at the MS, deal with two aspects of deep learning: a presentation of a concrete quaternionic convolutional neural network layer for image classification that features contrast invariance and a general overview of automatic learning aimed at steering the development of neural networks whose units process elements of a suitable algebra, such as a geometric algebra.. .The book fits, broadly speaking, within
出版日期Conference proceedings 2021
关键词Geometric calculi; Mathematical engineering; Multivector signal processing; Automatic learning; Efficien
版次1
doihttps://doi.org/10.1007/978-3-030-74486-1
isbn_softcover978-3-030-74488-5
isbn_ebook978-3-030-74486-1Series ISSN 2199-3041 Series E-ISSN 2199-305X
issn_series 2199-3041
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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https://doi.org/10.1007/978-3-030-74486-1Geometric calculi; Mathematical engineering; Multivector signal processing; Automatic learning; Efficien
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