Title :
A fast subspace pursuit for compressive sensing
Author :
Kun Tan ; Qun Wan ; Anmin Huang ; Juan Wang
Author_Institution :
Coll. of Electron. Eng., Univ. of Electron. Sci. & Technol. of China, Chengdu
Abstract :
A fast subspace pursuit algorithm is proposed to reconstruct sparse signals for compressive sensing. In order to reduce the computational cost, we symbolize the sampling matrix. As the result, multiplication is not required in the step of calculating the correlation. The analysis and simulation results reveal that the computational complexity of the proposed algorithm is much lower than that of the original subspace pursuit algorithm whereas the performance loss is fairly acceptable.
Keywords :
computational complexity; data compression; matrix algebra; signal reconstruction; compressive sensing; computational complexity; fast subspace pursuit; sampling matrix; sparse signal reconstruction; compressive sensing; fast algorithm; sparse signal reconstruction; subspace pursuit;
Conference_Titel :
Radar Conference, 2009 IET International
Conference_Location :
Guilin
Print_ISBN :
978-1-84919-010-7
