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【独家发布】【2016新书】Applied Matrix and Tensor Variate Data Analysis [推广有奖]

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牛尾巴 发表于 2016-7-28 11:22:55 |AI写论文

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图书名称:Applied Matrix and Tensor Variate Data Analysis

作者:Toshio Sakata

出版社:Springer Japan

页数:144
出版时间:2016
                           
语言:English

格式:pdf
内容简介:
This book provides comprehensive reviews of recent progress in matrix variate and tensor variate data analysis from applied points of view. Matrix and tensor approaches for data analysis are known to be extremely useful for recently emerging complex and high-dimensional data in various applied fields. The reviews contained herein cover recent applications of these methods in psychology (Chap. 1), audio signals (Chap. 2) , image analysis from tensor principal component analysis (Chap. 3), and image analysis from decomposition (Chap. 4), and genetic data (Chap. 5) . Readers will be able to understand the present status of these techniques as applicable to their own fields. In Chapter 5 especially, a theory of tensor normal distributions, which is a basic in statistical inference, is developed, and multi-way regression, classification, clustering, and principal component analysis are exemplified under tensor normal distributions. Chapter 6 treats one-sided tests under matrix variate and tensor variate normal distributions, whose theory under multivariate normal distributions has been a popular topic in statistics since the books of Barlow et al. (1972) and Robertson et al. (1988). Chapters 1, 5, and 6 distinguish this book from ordinary engineering books on these topics.

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关键词:Analysis Applied Variate Analysi matrix provides English reviews Matrix recent

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