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Activity Number: 88
Type: Invited
Date/Time: Sunday, July 31, 2016 : 6:00 PM to 8:00 PM
Sponsor: Section on Statistical Learning and Data Science
Abstract #319053
Title: Spectral Filtering for Spatial-Temporal Dynamics
Author(s): Tian Zheng* and Lu Meng
Companies: Columbia University and Columbia University
Keywords: Spatial-temporal ; time series ; spectral filtering ; lower-rank decomposition

Many applications generate spatial-temporal data that exhibit lower-rank smooth movements mixed with higher-rank noises. Separating the signal from the noise is important for us to visualize and understand the lower-rank movements. It is also often the case that the lower rank dynamics have multiple independent components that correspond to different trends or functionality of the system under study. In this presentation, we present a novel filtering method for identifying lower-rank dynamics and its components embedded in a high dimensional spatial-temporal system, with applications to climate data.

Authors who are presenting talks have a * after their name.

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