An Optimization Method of Deterministic Measurement Matrix in Distributed Compressed Video Sensing

DOI

10.2991/iceea-18.2018.38How to use a DOI?

Keywords

compressed sensing; orthogonal symmetric toeplitz matrix (OSTM); pseudorandom

Abstract

This electronic Compressed Sensing (CS) is a new theoretical framework for information acquisition and processing, which provides a new way for signal sampling. In order to solve the problem of the constraints of traditional Nyquist sampling theorem, CS based on the sparsity of signal, randomness of the measurement matrix and nonlinear optimization algorithm can achieve the compression and reconstruction of the signal. In the process of compressive sensing, the measurement matrix plays an important role in signal sampling and reconstruction. This construction is based on the orthogonal symmetric Toeplitz matrix in this paper. The pseudorandom feature of the deterministic measurement matrix is improved by pseudorandom loop construction method to ensure the random performance of the measurement matrix and optimize the compression measurement effect.

Copyright

© 2018, 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/).

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TY  - CONF
AU  - Jiawei Qin
AU  - Dengyin Zhang
AU  - Liang Xie
PY  - 2018/03
DA  - 2018/03
TI  - An Optimization Method of Deterministic Measurement Matrix in Distributed Compressed Video Sensing
BT  - Proceedings of the 2018 2nd International Conference on Electrical Engineering and Automation (ICEEA 2018)
PB  - Atlantis Press
SP  - 176
EP  - 179
SN  - 2352-5401
UR  - https://doi.org/10.2991/iceea-18.2018.38
DO  - 10.2991/iceea-18.2018.38
ID  - Qin2018/03
ER  -