Sparse Signal Recovery Through Regularized Orthogonal Matching Pursuit for WSNs Applications

被引：0
|
作者：
Goyal, Poonam [1 ]
Singh, Brahmjit [1 ]
机构：
[1] Natl Inst Technol Kurukshetra, Dept Elect & Commun Engn, Kurukshetra, Haryana, India
来源：
2019 6TH INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING AND INTEGRATED NETWORKS (SPIN) | 2019年
关键词：
Wireless sensor networks; compressed sensing regularized orthogonal matching pursuit; sparsity; PSNR; WIRELESS SENSOR NETWORKS;
D O I：
10.1109/spin.2019.8711716
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Regularized Orthogonal Matching Pursuit (ROMP) is an important greedy algorithm possessing both characteristics - speed and easier implementation. In this paper, we report on the efficacy of the ROMP for signal recovery through compressed sensing. Real-life temperature measurements are recorded utilizing an experimental test bed. The performance of the sparse signal recovery mechanism is measured in terms of peak-signal-to-noise-ratio and root-mean-square-error. Numerical results obtained through computer simulation analysed with reference to are generalized Orthogonal Matching Pursuit (gOMP). It is shown through results that ROMP outperforms the gOMP in case, accuracy is of prime concern in signal recovery.
引用
收藏
页码：461 / 465
页数：5
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