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arXiv · 2212.01721

Kronecker-structured Covariance Models for Multiway Data

Yu Wang·Zeyu Sun·Dogyoon Song·Alfred Hero
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Abstract

Many applications produce multiway data of exceedingly high dimension. Modeling such multi-way data is important in multichannel signal and video processing where sensors produce multi-indexed data, e.g. over spatial, frequency, and temporal dimensions. We will address the challenges of covariance representation of multiway data and review some of the progress in statistical modeling of multiway covariance over the past two decades, focusing on tensor-valued covariance models and their inference. We will illustrate through a space weather application: predicting the evolution of solar active regions over time.

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Yu Wang, Zeyu Sun, Dogyoon Song, Alfred Hero. 2022-12-04. Kronecker-structured Covariance Models for Multiway Data. https://arxiv.org/abs/2212.01721

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