Compressive Sampling

  • Date: 11/22/2007

Michael Lamoureux (University of Calgary)


Calgary Place Tower (Shell)


Modern signal processing aims to capture physical signals in the form of sound, images, and scientific data by collecting enormous numbers of digital samples and manipulating them in a computer. Conventionally, the rule of thumb for sampling is given by the Nyquist theorem: samples are collected at twice the rate of the bandwidth of the signal of interest. Compressive sampling suggests a more efficient approach, providing a method of capturing signals using much fewer samples and allowing the exact recovery of a signal or image at high resolution from this sparse sampling. This talk will present some of the basic ideas in compressive sampling, computational methods using optimization, and some applications.

Other Information: 

PIMS is presenting a series of lectures at the Calgary Place Tower 1 in downtown Calgary. These lectures, given by experts from the PIMS Universities, will focus on mathematical techniques and applications relevant to the oil and gas industry and will demonstrate the utility and beauty of applied mathematics. The talks are aimed at a general audience. Attendance may qualify for APEGGA Professional Development Hours.