RT Conference Proceedings
T1 From seismography to compressed sensing and back: a brief history of optimization-based signal processing
A1 Fernández Granda, Carlos
K1 Sismometría
AB In this talk we provide an overview of the history of l1-norm minimization applied to underdetermined inverse problems. In the 70s and 80s geophysicists proposed using l1-norm minimization for deconvolution from bandpass data in reflection seismography. In the 2000s, inspired by this approach and by magnetic resonance imaging, a method to provably recover sparse signals from random projections, known as compressed sensing, was developed. Theoretical insights used to analyze compressed sensing have recently been adapted to understand the potential and limitations of l1-norm minimization for deterministic problems. These include super-resolution from low-pass data and the deconvolution problem that originally motivated the geophysicists.
YR 2017
FD 2017-03-17
LK http://hdl.handle.net/10630/13322
UL http://hdl.handle.net/10630/13322
LA eng
NO Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech.
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 31 ene 2026