Sampling Theorems for Signals From the Union of Finite-Dimensional Linear Subspaces

Abstract

Compressed sensing is an emerging signal acquisition technique that enables signals to be sampled well below the Nyquist rate, given that the signal has a sparse representation in an orthonormal basis. In fact, sparsity in an orthonormal basis is only one possible signal model that allows for sampling strategies below the Nyquist rate. In this paper, we… (More)
DOI: 10.1109/TIT.2009.2013003

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@article{Blumensath2009SamplingTF, title={Sampling Theorems for Signals From the Union of Finite-Dimensional Linear Subspaces}, author={Thomas Blumensath and Mike E. Davies}, journal={IEEE Transactions on Information Theory}, year={2009}, volume={55}, pages={1872-1882} }