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Off-The-Grid Spectral Compressed Sensing With Prior Information

2013/11/05 by Kumar Vijay Mishra, Mishra, Kumar Vijay, Myung Cho +5 · 1 citation
Computer Science · Mathematics · #FOS: Computer and information sciences #Information Theory (cs.IT) #cs.IT #math.IT

paper · pdf · doi:10.48550/arxiv.1311.0950

5 pages, 4 figures

arxiv created 2013/11/07 · arxiv updated 2013/11/08

Abstract

Recent research in off-the-grid compressed sensing (CS) has demonstrated that, under certain conditions, one can successfully recover a spectrally sparse signal from a few time-domain samples even though the dictionary is continuous. In this paper, we extend off-the-grid CS to applications where some prior information about spectrally sparse signal is known. We specifically consider cases where a few contributing frequencies or poles, but not their amplitudes or phases, are known a priori. Our results show that equipping off-the-grid CS with the known-poles algorithm can increase the probability of recovering all the frequency components.

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