__Claremont Graduate University__ | __Claremont McKenna__ | __Harvey Mudd__ | __Pitzer__ | __Pomona__ | __Scripps__

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Copyright © 2011 Claremont Center for the Mathematical Sciences

When

Start: 10/12/2015 - 4:15pm

End : 10/12/2015 - 5:15pm

End : 10/12/2015 - 5:15pm

Category

Applied Math Seminar

Speaker

Tina Woolf (CGU)

Abstract

Traditional signal processing schemes sample signals at a high rate and immediately discard most of the information during the compression process. Compressed sensing is a new field that improves this by directly sensing the signal in compressed form using few nonadaptive, linear measurements. Adaptive sensing, which allows the selection of the next measurement based on previous observations, significantly improves signal recovery when arbitrary linear measurements can be constructed. However, in practice, the types of measurements that can be acquired are limited. In this talk, we will discuss recent results on the limitations and advantages of adaptive sensing when the measurements are constrained to belong to a finite set of allowable measurement vectors.

Where

Emmy Noether Room (Pomona), Millikan 1021