@inproceedings{328a2ddcd7d84415a4abd8276bb8ff81,
title = "Prosparse denoise: Prony's based sparse pattern recovery in the presence of noise",
abstract = "We present a novel algorithm - ProSparse Denoise - that can solve the sparsity recovery problem in the presence of noise when the dictionary is the union of Fourier and identity matrices. The algorithm is based on a proper use of Cadzow routine and Prony's method and exploits the duality of Fourier and identity matrices. The algorithm has low complexity compared to state of the art algorithms for sparse recovery since it relies on the Fast Fourier Transform (FFT) algorithm. We provide conditions on the noise that guarantees the correct recovery of the sparsity pattern. Our approach outperforms state of the art algorithms such as Basis Pursuit De-noise and Subspace Pursuit when the dictionary is the union of Fourier and identity matrices.",
keywords = "Prony's method, Sparse representation, denoising, union of bases",
author = "Jon Onativia and Lu, \{Yue M.\} and Dragotti, \{Pier Luigi\}",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 41st IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 ; Conference date: 20-03-2016 Through 25-03-2016",
year = "2016",
month = may,
day = "18",
doi = "10.1109/ICASSP.2016.7472445",
language = "English",
series = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "4084--4088",
booktitle = "2016 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Proceedings",
address = "United States",
}