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An l0 norm based method for frequency estimation from irregularly sampled data

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2 Author(s)
Md Mashud Hyder ; School of Electrical Engineering and Computer Science, University of Newcastle, Callaghan, NSW 2308, Australia ; Kaushik Mahata

We present a frequency estimation method based on a sparse representation of irregular samples with an overcomplete basis. We enforce sparsity by imposing penalties based on an approximate ℓ0- norm. A number of recent theoretical results on compressed sensing justify this choice. Explicitly enforcing the sparsity of the representation is motivated by a desire to obtain a sharp estimate of the frequency spectrum that exhibits super-resolution. Our formulation leads to an optimization problem, which we solve efficiently in an iterative algorithm. The simulation results demonstrate that that the proposed algorithm outperforms several other state-of-art methods.

Published in:

2010 IEEE International Conference on Acoustics, Speech and Signal Processing

Date of Conference:

14-19 March 2010