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Vol. 165, Issue 2, February 2014, pp. 131-136

 

Bullet

 

Quasi Gradient Projection Algorithm for Sparse Reconstruction in Compressed Sensing
 

Xin Meng, Minhua Zhang

School of Computer and Communication Engineering, Tianjin University of Technology, Tianjin 300384, China
Tel.: 022-60216865, fax: 022-60216906

E-mail: mengxin@tjut.edu.cn

 

Received: 29 October 2013 /Accepted: 27 December 2013 /Published: 28 February 2014

Digital Sensors and Sensor Sysstems

 

Abstract: Compressed sensing is a novel signal sampling theory under the condition that the signal is sparse or compressible. The existing recovery algorithms based on the gradient projection can either need prior knowledge or recovery the signal poorly. In this paper, a new algorithm based on gradient projection is proposed, which is referred as Quasi Gradient Projection. The algorithm presented quasi gradient direction and two step sizes schemes along this direction. The algorithm doesn’t need any prior knowledge of the original signal. Simulation results demonstrate that the presented algorithm cans recovery the signal more correctly than GPSR which also don’t need prior knowledge. Meanwhile, the algorithm has a lower computation complexity.

 

Keywords: Compressed sensing, Gradient projection, Quasi gradient,

 

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