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.
Last updated October 10, 2013, at 01:33 PM