Future Generation Computer Systems
Blind multiband signal reconstruction: compressed sensing for analog signals
IEEE Transactions on Signal Processing
Compressed sensing of analog signals in shift-invariant spaces
IEEE Transactions on Signal Processing
Spectral analysis of nonuniformly sampled data -- a review
Digital Signal Processing
Beyond Nyquist: efficient sampling of sparse bandlimited signals
IEEE Transactions on Information Theory
Regularized sampling of multiband signals
IEEE Transactions on Signal Processing
Sampling theorem for multidimensional, multiband signals
CONTROL'05 Proceedings of the 2005 WSEAS international conference on Dynamical systems and control
Reconstruction of compressed samples in shift-invariant space base on matrix factorization
Computers and Electrical Engineering
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We examine the problem of periodic nonuniform sampling of a multiband signal and its reconstruction from the samples. This sampling scheme, which has been studied previously, has an interesting optimality property that uniform sampling lacks: one can sample and reconstruct the class ℬ(ℱ) of multiband signals with spectral support ℱ, at rates arbitrarily close to the Landau (1969) minimum rate equal to the Lebesgue measure of ℱ, even when ℱ does not tile R under translation. Using the conditions for exact reconstruction, we derive an explicit reconstruction formula. We compute bounds on the peak value and the energy of the aliasing error in the event that the input signal is band-limited to the “span of ℱ” (the smallest interval containing ℱ) which is a bigger class than the valid signals ℬ(ℱ), band-limited to ℱ. We also examine the performance of the reconstruction system when the input contains additive sample noise