Special Session 97: New Advances in Structured Signal Recovery

A Generalized Matrix Separation Problem

Xuemei Chen
University of North Carolina Wilmington
USA
Co-Author(s):    
Abstract:
The problem of separating a known matrix into its low rank and sparse components have found numerous applications in imaging, multimedia processing, statistical modeling, etc. In this talk we will explore this problem in a more complicated setting where the sparse component has been masked by a linear transformation. This problem was motivated by an electrodermal activity signal decomposition problem, but we believe it has a wider appeal.