Sampling Theorems for Signals from the Union of Linear Subspaces .

@inproceedings{Blumensath2008SamplingTF,
  title={Sampling Theorems for Signals from the Union of Linear Subspaces .},
  author={Thomas Blumensath and Mike E. Davies},
  year={2008}
}
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 consider a more general signal model and assume signals that live on or close to the union of linear subspaces of low dimension. We present… CONTINUE READING
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