Proceedings of the 2016 7th International Conference on Education, Management, Computer and Medicine (EMCM 2016)

Improvement of Dirichlet Observation Matrix based on Super Prime Numbers

Authors
Huanan Yu, Xin Zhang, Yao Du
Corresponding Author
Huanan Yu
Available Online February 2017.
DOI
https://doi.org/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.
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Proceedings
2016 7th International Conference on Education, Management, Computer and Medicine (EMCM 2016)
Part of series
Advances in Computer Science Research
Publication Date
February 2017
ISBN
978-94-6252-297-8
ISSN
2352-538X
DOI
https://doi.org/10.2991/emcm-16.2017.53How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

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  - 2016 7th International Conference on Education, Management, Computer and Medicine (EMCM 2016)
PB  - Atlantis Press
SN  - 2352-538X
UR  - https://doi.org/10.2991/emcm-16.2017.53
DO  - https://doi.org/10.2991/emcm-16.2017.53
ID  - Yu2017/02
ER  -