Compressed sampling: toward new ways of going from A to D

Pierre Vandergheynst, Signal Processing Laboratory (LTS2), Swiss Federal Institute of Technology, Lausanne

Abstract: Recently there has been a lot of buzz in the applied maths and signal processing communities about a new theory called Compressed Sensing or Compressive Sampling (CS). The central result of CS asserts that a large class of signals can be sampled far below the Shannon-Nyquist rate with simple linear strategies that could be efficiently implemented in hardware. This would mean new ways to perform A/D conversion and, in a larger scope, new ways to manipulate signals with a new emphasis on analog processing.

In this talk, I will review the CS theory, describing which signals can be sampled efficiently and why, intuitively, the theory holds. I will also describe the family of new algorithms needed to implement CS and will review some recent applications.

About the speaker: Dr. Pierre Vandergheynst received the M.S. degree in physics and the Ph.D. degree in mathematical physics from the Université catholique de Louvain, Louvain-la-Neuve, Belgium, in 1995 and 1998, respectively. From 1998 to 2001, he was a Postdoctoral Researcher with the Signal Processing Laboratory, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland. He was Assistant Professor at EPFL (2002-2007), where he is now an Associate Professor. His research focuses on harmonic analysis, sparse approximations and mathematical image processing with applications to higher dimensional, complex data processing. He was co-Editor-in-Chief of Signal Processing (2002-2006) and is Associate Editor of the IEEE Transactions on Signal Processing (2007-present). He has been on the Technical Committee of various conferences and was Co-General Chairman of the EUSIPCO 2008 conference. Pierre Vandergheynst is the author or co-author of more than 50 journal papers, one monograph and several book chapters. He is a senior member of the IEEE, a laureate of the Apple ARTS award and holds seven patents.