PIMS/Shell Lunchbox Lecture: Compressed Sensing: Theory, Applications and Extensions

  • Date: 02/26/2015
Ben Adcock, Simon Fraser University

Calgary Place Tower (Shell)


Compressed Sensing: Theory, Applications and Extensions


A video of this event is available on mathtube.org.


Many problems in science and engineering require the reconstruction of an object - an image or signal, for example - from a collection of measurements.  Due to time, cost or other constraints, one is often severely limited by the amount of data that can be collected.  Compressed sensing is a mathematical theory and set of techniques that aim to improve reconstruction quality from a given data set by leveraging the underlying structure of the unknown object; specifically, its sparsity.  


In this talk I will commence with an overview of the fundamentals of compressed sensing and discuss some of its applications.  However, I will next explain that, despite the large and growing body of literature on compressed sensing, many of these applications do not fit into the standard framework.  I will then describe a more general framework for compressed sensing which aims to bridge this gap.  Finally, I will show that this new framework is not just useful in explaining existing applications of compressed sensing.  The new insight it brings leads to substantially better compressed sensing-based approaches than the current state-of-the-art in a number of applications.


Other Information: 

Location: Calgary Place Tower 1 (330 5th Avenue SW), Room 1116


Time: 12:00-1:00 pm





PIMS is grateful for the support of Shell Canada Limited, Alberta
Enterprise and Advanced Education, and the University of Calgary for
their support of this series of lectures.