CORDIS Project
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This project focuses on developing theories and algorithms for sparse sampling in signal processing. It aims to improve methods for acquiring continuous-time signals from discrete samples, impacting areas like data compression and imaging.
Signal representations with Fourier and wavelet bases are central to signal processing and communications.
Non-linear approximation methods in such bases are key for problems like denoising, compression and inverse problems.
Recently, the idea that signals that are sparse in some domain can be acquired at low sampling density has generated strong interest, under various names like compressed sensing, compressive sampling and sparse sampling.
We aim to study the central problem of acquiring conti…
ECOLE POLYTECHNIQUE FEDERALE DE LAUSANNE
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