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 :
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