**Title**: "Continuous parameter estimation from compressive samples"

**Speaker**: Prasad Sudhakar (ICTEAM/ELEN, UCL)

**Location**: "Shannon" Seminar Room (a105)
Place du Levant 3, Maxwell Building, 1st floor

**Date / Time (duration)**: October 9, **10h00** (~ 45')

**Abstract:** For several applications, it is sufficient only to extract a few parameters of a signal, from its compressive measurements, instead of having a full reconstruction, thereby saving a lot of computational effort. Often, the underlying parameters that characterize the signal are drawn from a continuous space. However, the standard compressive sensing formalism is discrete in nature and hence the parameter estimates are confined to a predefined grid. In order to go off the grid, one has to exploit the underlying continuous model and perform either gradient descent or interpolation. In this talk, I will consider a very simple signal model and describe how to estimate continuous parameters from compressive samples.

(slides)

ISPSeminar