Title :
On estimating the loss of signal-to-noise ratio in compressive sensing based systems
Author :
Yaming Wang ; Laming Chen ; Yuantao Gu
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Maryland, College Park, MD, USA
Abstract :
The up-to-date researches focused on compressive sensing (CS) have indicated that a CS-based system could be very sensitive to signal noise which contaminates the input signal prior to measurement. In this paper, it is demonstrated that the SNR loss of the recovered signal can be estimated by the subsampling rate. The conditions based on which the proposed estimator is applied are theoretical analyzed and numerically verified.
Keywords :
compressed sensing; signal sampling; compressive sensing based systems; estimator; signal noise; signal to noise ratio; subsampling rate; Accuracy; Approximation methods; Compressed sensing; Loss measurement; Pollution measurement; Signal to noise ratio; SNR loss; compressive sensing; signal noise; subsampling rate;
Conference_Titel :
Signal and Information Processing (ChinaSIP), 2013 IEEE China Summit & International Conference on
Conference_Location :
Beijing
DOI :
10.1109/ChinaSIP.2013.6625296
