DocumentCode
178759
Title
Gridless compressive sensing
Author
Panahi, A. ; Viberg, M.
Author_Institution
Dept. of Signals & Syst., Chalmers Univ. of Technol., Gothenburg, Sweden
fYear
2014
fDate
4-9 May 2014
Firstpage
3385
Lastpage
3389
Abstract
The effect of off-grid atoms has become the prominent problem in application of the Compressed Sensing (CS) techniques to the cases where there is an underlying continuous parametrization. In this work, we develop a generalizing CS framework which shows that sampling to a finite grid is not necessary toward compressive estimation. We propose an alternative procedure over infinite dictionaries, which we show to be theoretically consistent in many cases of interest and then propose a robust implementation. We illustrate the general properties of our technique in some difficult practical instances of frequency estimation.
Keywords
compressed sensing; frequency estimation; signal sampling; CS framework; compressive estimation; frequency estimation; gridless compressive sensing; infinite dictionaries; off-grid atoms; Compressed sensing; Convex functions; Dictionaries; Estimation; Signal to noise ratio; Vectors;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on
Conference_Location
Florence
Type
conf
DOI
10.1109/ICASSP.2014.6854228
Filename
6854228
Link To Document