Compressed Sensing to Power Quality Signal with Orthogonal Matching Pursuit Method
- 10.2991/icmmita-16.2016.12How to use a DOI?
- Compressed sensing; Power quality; Sparse representation; Orthogonal matching pursuit
Compressed sensing is a new data compression method which can recover a sparse or compressible signal from a small number of linear and non-adaptive measurements. To solve the problems of high sampling rate and massive data storage faced by traditional collection and compression methods of power quality, compressed sensing algorithm is used in the paper. Gaussian random measurement matrix is used to complete the compressed sampling. The orthogonal matching pursuit method is adopted in the reconstruction processes. Simulation show that The SNR of the reconstruction of harmonics signal using compressed sensing is higher than the traditional compression method such as wavelet transform and DCT transform.
- © 2017, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Hua Ouyang AU - Zhonglin Yang AU - Hui Li PY - 2017/01 DA - 2017/01 TI - Compressed Sensing to Power Quality Signal with Orthogonal Matching Pursuit Method BT - Proceedings of the 2016 4th International Conference on Machinery, Materials and Information Technology Applications PB - Atlantis Press SP - 60 EP - 63 SN - 2352-538X UR - https://doi.org/10.2991/icmmita-16.2016.12 DO - 10.2991/icmmita-16.2016.12 ID - Ouyang2017/01 ER -