Title :
Fusion of Greedy Pursuits for compressed sensing signal reconstruction
Author :
Ambat, Sooraj K. ; Chatterjee, Saikat ; Hari, K.V.S.
Author_Institution :
Dept. of Electr. Commun. Eng., Indian Inst. of Sci., Bangalore, India
Abstract :
Greedy Pursuits are very popular in Compressed Sensing for sparse signal recovery. Though many of the Greedy Pursuits possess elegant theoretical guarantees for performance, it is well known that their performance depends on the statistical distribution of the non-zero elements in the sparse signal. In practice, the distribution of the sparse signal may not be known a priori. It is also observed that performance of Greedy Pursuits degrades as the number of available measurements decreases from a threshold value which is method dependent. To improve the performance in these situations, we introduce a novel fusion framework for Greedy Pursuits and also propose two algorithms for sparse recovery. Through Monte Carlo simulations we show that the proposed schemes improve sparse signal recovery in clean as well as noisy measurement cases.
Keywords :
Monte Carlo methods; compressed sensing; signal reconstruction; statistical analysis; Monte Carlo simulation; compressed sensing signal reconstruction; greedy pursuits; noisy measurement; nonzero element; sparse signal distribution; sparse signal recovery; statistical distribution; threshold value; Atomic measurements; Compressed sensing; Joints; Matching pursuit algorithms; Noise measurement; Signal processing; Vectors; Compressed sensing; Fusion; Greedy Pursuits; Sparse Recovery;
Conference_Titel :
Signal Processing Conference (EUSIPCO), 2012 Proceedings of the 20th European
Print_ISBN :
978-1-4673-1068-0