Applied Matrix and Tensor Variate Data Analysis
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 field...
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| Language: | English |
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Tokyo :
Springer Japan : Imprint: Springer,
2016.
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| Edition: | 1st ed. 2016. |
| Series: | JSS Research Series in Statistics,
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| Online Access: | https://doi.org/10.1007/978-4-431-55387-8 |
Table of Contents:
- 1 Three-Way Principal Component Analysis with its Applications to Psychology (Kohei Adachi)
- 2 Non-negative matrix factorization and its variants for audio signal processing (Hirokazu Kameoka)
- 3 Generalized Tensor PCA and its Applications to Image Analysis (Kohei Inoue)
- 4 Matrix Factorization for Image Processing (Noboru Murata)
- 5 Arrays Normal Model and Incomplete Array Variate Observations (Deniz Akdemir)
- 6 One-sided Tests for Matrix Variate Normal Distribution (Manabu Iwasa and Toshio Sakata).