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A new method to compute optimal periodic sampling patterns

Arash Owrang (Institutionen för signaler och system) ; Mats Viberg (Institutionen för signaler och system, Signalbehandling) ; Mohsen Nosratinia (Institutionen för signaler och system, Signalbehandling) ; Moslem Rashidi Avendi (Institutionen för signaler och system, Signalbehandling)
2011 Digital Signal Processing and Signal Processing Education Meeting, DSP/SPE 2011 - Proceedings p. 259-264 . (2011)
[Konferensbidrag, övrigt]

It is possible to reconstruct a signal from cyclic nonuniform samples and thus take advantage of a lower sampling rate than the Nyquist rate. However, this has the potential drawback of amplifying signal perturbations, e.g. due to noise and quantization. We propose an algorithm based on sparse reconstruction techniques, which is able to find the sparsest sampling pattern that permits perfect reconstruction of the sampled signal. The result of our algorithm with a proper constraint values is a sparse subset of samples that results in an ideal condition number for its equivalent sub-DFT matrix. Besides, our algorithm has low complexity in terms of computation. The method is illustrated by simulations for a sparse multi band signal.

Nyckelord: Basis Pursuit, condition number, greedy search, nonuniform sampling, Sparse approximation



Denna post skapades 2011-06-01. Senast ändrad 2016-07-25.
CPL Pubid: 141322

 

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