Dynamic subspace pursuit

Author

Zachariah, Dave ; Chatterjee, Saikat ; Jansson, Magnus

Author_Institution

ACCESS Linnaeus Centre, KTH - R. Inst. of Technol., Stockholm, Sweden

fYear

2012

fDate

25-30 March 2012

Firstpage

3605

Lastpage

3608

Abstract

For compressive sensing of dynamic sparse signals, we develop an iterative greedy search algorithm based on subspace pursuit (SP) that can incorporate sequential predictions, thereby taking advantage of its low complexity while improving recovery performance by exploiting correlations described by a state space model. The algorithm, which we call dynamic subspace pursuit (DSP), is presented and experimentally validated. It exhibits a graceful degradation at deteriorating signal conditions while capable of yielding substantial performance gains as conditions improve.

Keywords

computational complexity; greedy algorithms; iterative methods; search problems; signal reconstruction; compressive sensing; dynamic sparse signals; dynamic subspace pursuit; iterative greedy search algorithm; state space model; Compressed sensing; Correlation; Digital signal processing; Heuristic algorithms; Matching pursuit algorithms; Prediction algorithms; Vectors; Compressive sensing; recursive reconstruction; sparse reconstruction;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech and Signal Processing (ICASSP), 2012 IEEE International Conference on

Conference_Location

Kyoto

ISSN

1520-6149

Print_ISBN

978-1-4673-0045-2

Electronic_ISBN

1520-6149

Type

conf

DOI

10.1109/ICASSP.2012.6288696

Filename

6288696