Department of Mathematics

Applied Mathematics

  •  Sensor fusion via two types of diffusion — with sleep dynamics and fetal health as examples.
  •  04/20/2018
  •  4:10 PM - 5:00 PM
  •  C304 Wells Hall
  •  Hau-Tieng Wu, Duke University

Quantifying the intrinsic structure from a given massive dataset, which is often nonlinear and complex, is a common challenge shared in almost all scientific fields, including data science. The problem is becoming more challenging when the data are from multiple sensors with heterogenous data types. The diffusion geometry is a flexible framework for this challenge that has led to several convincing results with solid theoretical backup. We will discuss how to apply the diffusion geometry, particularly the alternating diffusion and commutator, to deal with the sensor fusion problem. Its application to the sleep dynamics analysis and fetal electrocardiogram analysis will be discussed.



Department of Mathematics
Michigan State University
619 Red Cedar Road
C212 Wells Hall
East Lansing, MI 48824

Phone: (517) 353-0844
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College of Natural Science