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Titlebook: Functional and Shape Data Analysis; Anuj Srivastava,Eric P. Klassen Textbook 2016 Springer-Verlag New York 2016 Riemannian methods.shape a

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書目名稱Functional and Shape Data Analysis
編輯Anuj Srivastava,Eric P. Klassen
視頻videohttp://file.papertrans.cn/350/349864/349864.mp4
概述Presents a complete and detailed exposition on statistical analysis of shapes that includes appendices, background material, and exercises, making this text a self-contained reference.Addresses and ex
叢書名稱Springer Series in Statistics
圖書封面Titlebook: Functional and Shape Data Analysis;  Anuj Srivastava,Eric P. Klassen Textbook 2016 Springer-Verlag New York 2016 Riemannian methods.shape a
描述This textbook for courses on function data analysis and shape data analysis describes how to define, compare, and mathematically represent shapes, with a focus on statistical modeling and inference. It is aimed at graduate students in analysis in statistics, engineering, applied mathematics, neuroscience, biology, bioinformatics, and other related areas. The interdisciplinary nature of the broad range of ideas covered—from introductory theory to algorithmic implementations and some statistical case studies—is meant to familiarize graduate students with an array of tools that are relevant in developing computational solutions for shape and related analyses.These tools, gleaned from geometry, algebra, statistics, and computational science, are traditionally scattered across different courses, departments, and disciplines; .Functional and Shape Data Analysis .offers a unified, comprehensive solution by integrating the registration problem into shape analysis, better preparing graduate students for handling future scientific challenges..Recently, a data-driven and application-oriented focus on shape analysis has been trending. This text offers a self-contained treatment of this new gen
出版日期Textbook 2016
關(guān)鍵詞Riemannian methods; shape analysis; function data analysis; curves; mathematical representations; vector-
版次1
doihttps://doi.org/10.1007/978-1-4939-4020-2
isbn_softcover978-1-4939-8155-7
isbn_ebook978-1-4939-4020-2Series ISSN 0172-7397 Series E-ISSN 2197-568X
issn_series 0172-7397
copyrightSpringer-Verlag New York 2016
The information of publication is updating

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