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University of Cambridge > Talks.cam > Cambridge Analysts' Knowledge Exchange (C.A.K.E.) > A nonlinear approach to generalized sampling

## A nonlinear approach to generalized samplingAdd to your list(s) Download to your calendar using vCal - Clarice Poon (CCA)
- Wednesday 08 May 2013, 16:00-17:00
- MR14, Centre for Mathematical Sciences.
If you have a question about this talk, please contact Martin Taylor. One of the central problems of sampling theory is the reconstruction of an image or a signal from a collection of measurements. Typically, this problem may be modeled in a Hilbert space setting and measurements are taken with respect to some set of vectors, such as some Fourier basis. Generalized sampling is a framework for obtaining reconstructions in arbitrary spaces without constraints on the type of measurements. In my talk, I will present generalized sampling as an l^1 minimization problem and apply this framework to the reconstruction of wavelets coefficients from Fourier samples. I will also briefly discuss some implications of generalized sampling for the use of variable density sampling schemes in compressed sensing. This talk is part of the Cambridge Analysts' Knowledge Exchange (C.A.K.E.) series. ## This talk is included in these lists:- All CMS events
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- MR14, Centre for Mathematical Sciences
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