Improvement of Dirichlet Observation Matrix based on Super Prime Numbers

DOI

10.2991/emcm-16.2017.53How to use a DOI?

Keywords

Compressed sensing; Dirichlet; Super prime; Reconstruction quality; Observation matrix

Abstract

The reconstruction quality of the signal is directly determined by the observation matrix in the sense of signal compression. The observation matrix has a strong randomness to ensure the quality of the signal reconstruction, but the hardware implementation of the random observation matrix is more difficult. The certainty observation matrix is easy to be realized, but the reconstruction quality is poor. In order to balance the randomness and the realization of the observation matrix, this paper proposes the use of super prime numbers to generate pseudo-random sequence, which can make up the deficiency of the non randomness of the deterministic observation matrix. Combined with the structure characteristics of Dirichlet observation matrix to design an observation matrix. Compared to the Gaussian random observation matrix, Dirichlet observation matrix and based on super prime Dirichlet observation matrix, the quality of the reconstructed signal was improved significantly and easy to be realized with hardware.

Copyright

© 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/).

Download article (PDF)

TY  - CONF
AU  - Huanan Yu
AU  - Xin Zhang
AU  - Yao Du
PY  - 2017/02
DA  - 2017/02
TI  - Improvement of Dirichlet Observation Matrix based on Super Prime Numbers
BT  - Proceedings of the 2016 7th International Conference on Education, Management, Computer and Medicine (EMCM 2016)
PB  - Atlantis Press
SP  - 269
EP  - 273
SN  - 2352-538X
UR  - https://doi.org/10.2991/emcm-16.2017.53
DO  - 10.2991/emcm-16.2017.53
ID  - Yu2017/02
ER  -