A new method to compute optimal periodic sampling patterns
Conference contribution, 2011

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.

Sparse approximation

greedy search

nonuniform sampling

condition number

Basis Pursuit

Author

Arash Owrang

Chalmers, Signals and Systems

Mats Viberg

Chalmers, Signals and Systems, Signalbehandling och medicinsk teknik, Signal Processing

Mohsen Nosratinia

Chalmers, Signals and Systems, Signalbehandling och medicinsk teknik, Signal Processing

Moslem Rashidi Avendi

Chalmers, Signals and Systems, Signalbehandling och medicinsk teknik, Signal Processing

2011 Digital Signal Processing and Signal Processing Education Meeting, DSP/SPE 2011 - Proceedings

259-264

Subject Categories

Signal Processing

DOI

10.1109/DSP-SPE.2011.5739222

ISBN

978-161284227-1

More information

Created

10/7/2017