Bisection Subspace Pursuit Algorithm for Compressive Sensing

Autor: Fang Wang, Xiao Jing Li, Dong Mei Li, Kai Liang Zhang, Lei Zhou, Sheng Fa Liang
Rok vydání: 2015
Předmět:
Zdroj: Applied Mechanics and Materials. :1256-1260
ISSN: 1662-7482
DOI: 10.4028/www.scientific.net/amm.713-715.1256
Popis: A novel greedy algorithm for blind CS recovery without prior knowledge of sparsity, called the Bisection Subspace Pursuit (BiSP) is introduced. The most outstanding feature of the BiSP is that it adopts the bisection method to adaptively estimate the sparsity of target signal, which means that no prior knowledge of sparsity is needed. Simulation results demonstrate that the BiSP not only retains comparable recovery accuracy with CoSaMP, SP and SAMP, but also outperforms the SAMP in terms of complexity when sparsity of signal is large. This makes the BiSP a competitive candidate for many practical situations.
Databáze: OpenAIRE