A numerical implementation of gridless compressed sensing
Paper in proceeding, 2015

Atomic norm denoising has been recently introduced as a generalization of the Least Absolute Shrinkage and Selection Operator (LASSO) to overcome the problem of off-grid parameters. The method has been found to possess many interesting theoretical properties. However, its implementation has been only discussed in a special case of spectral line estimation by uniform sampling. In this paper, we propose a general numerical method to solve the atomic norm denoising problem. The complexity of the proposed algorithm is proportional to the complexity of a single-parameter search in the parameter space and thus in many interesting cases, including frequency estimation it enjoys fast realization.

LASSO

implementation

Atomic norm

multiple parameter estimation

Author

Ashkan Panahi

Chalmers, Signals and Systems, Signal Processing and Biomedical Engineering

Mats Viberg

Chalmers, Signals and Systems, Signal Processing and Biomedical Engineering

B. Hassibi

California Institute of Technology (Caltech)

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

15206149 (ISSN)

Vol. 2015-August 3342-3346
978-1-4673-6997-8 (ISBN)

Subject Categories

Electrical Engineering, Electronic Engineering, Information Engineering

DOI

10.1109/ICASSP.2015.7178590

ISBN

978-1-4673-6997-8

More information

Latest update

8/8/2023 6