论文标题
KRONECKER结构的协方差模型
Kronecker-structured Covariance Models for Multiway Data
论文作者
论文摘要
许多应用程序产生了极高维度的多路数据。建模这种多通道数据在多通道信号和视频处理中很重要，其中传感器会产生多点数数据，例如超过空间，频率和时间维度。我们将应对多路数据的协方差表示的挑战，并回顾过去二十年来多路协方差的统计建模的一些进展，重点介绍了张量值的协方差模型及其推断。我们将通过太空天气应用程序进行说明：预测太阳活动区域随时间的演变。
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.
