Scientific Computing, Applied and Industrial Mathematics (SCAIM) Seminar: Dr Sui Tang

  • Date: 01/08/2019
  • Time: 12:30
Dr Sui Tang, Johns Hopkins University

University of British Columbia


Dynamical Sampling


Dynamical sampling is a new area in sampling theory that deals with processing a time series of evolving signals  {A^nx, n=0,1,2,...} and aims at recovering the signal x  from its coarsely sampled evolving states.  In the talk,  I will present why and how the temporal dynamics can compensate for insufficient spatial information.  In particular, I will show how the dynamical sampling problem is linked to compressed sensing. Another more challenging problem arises when the operator A is also unknown and we want to recover both x and A.  This problem exhibits features that occur similar to many fundamental problems in engineering such as deconvolution, and super-resolution and the matrix completion problem. We propose reconstruction algorithms with provable guarantees by employing ideas from the classical Prony method, matrix pencil method, and the ESPRIT method.  Finally, I will conclude with some open questions and future research directions.

Other Information: 

Location: ESB 4133 (PIMS lounge)