Recovering tensor data from incomplete measurement via compressive sampling

Authors:
Jason R. Holloway;Carmeliza Navasca
Affiliations:
Department of Electrical Engineering, Clarkson University, Potsdam, New York;Department of Mathematics, Clarkson University, Potsdam, New York
Venue:
Asilomar'09 Proceedings of the 43rd Asilomar conference on Signals, systems and computers
Year:
2009

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Abstract

We present a method for recovering tensor data from few measurements. By the process of vectorizing a tensor, the compressed sensing techniques are readily applied. Our formulation leads to three l1 minimizations for third order tensors. We demonstrate our algorithm on many random tensors with varying dimensions and sparsity.