Title :
Soft-thresholding Orthogonal Matching Pursuit for efficient signal reconstruction
Author :
Guoxian Huang ; Lei Wang
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Connecticut, Storrs, CT, USA
Abstract :
In this paper, we propose a Soft-thresholding Orthogonal Matching Pursuit (ST-OMP) technique for efficient signal reconstruction in compressive sensing applications. The proposed ST-OMP recovers less significant signal elements using a low-complexity procedure without sacrificing much reconstruction quality. We apply the proposed ST-OMP in systems powered by non-deterministic renewable energy sources. The threshold of employing the efficient reconstruction is made dynamically adjustable according to the performance requirements and energy levels. Simulation results demonstrate that the ST-OMP can achieve good recovery performance while significantly reducing the energy consumption as compared to the original OMP implementation.
Keywords :
compressed sensing; energy consumption; renewable energy sources; signal reconstruction; ST-OMP technique; compressive sensing applications; energy consumption; energy levels; low-complexity procedure; nondeterministic renewable energy sources; signal elements; signal reconstruction; soft-thresholding orthogonal matching pursuit; Computational complexity; Energy consumption; Matching pursuit algorithms; Renewable energy sources; Sensors; Signal reconstruction; Vectors; Compressed sensing; Energy efficiency; Renewable Energy; Signal reconstruction; Soft-thresholding;
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on
Conference_Location :
Vancouver, BC
DOI :
10.1109/ICASSP.2013.6638114