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Extracting bits from analog samples: in pursuit of optimality

Presented by: 
Sinan Güntürk Courant Institute of Mathematical Sciences, New York University
Date: 
Thursday 20th June 2019 - 09:00 to 09:50
Venue: 
INI Seminar Room 1
Abstract: 
Sampling theorems, linear or non-linear, provide the basis for obtaining digital representations of analog signals, but often it is not obvious how to quantize these samples in order to achieve the best rate-distortion trade off possible, especially in the presence of redundancy. We will present a general approach called "distributed beta encoding" which can achieve superior (and often near-optimal) rate-distortion performance in a wide variety of sampling scenarios. These will include some classical problems in the linear setting such as Fourier and Gabor sampling, and some others in the nonlinear setting, such as compressive sampling, spectral super-resolution, and phase retrieval.
University of Cambridge Research Councils UK
    Clay Mathematics Institute London Mathematical Society NM Rothschild and Sons