The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
압축 감지는 효과적인 압축 알고리즘입니다. 이는 분산 센서 네트워크(DSN)에서 신호를 측정하는 데 널리 사용됩니다. DSN의 제한된 자원을 고려할 때 DSN에 사용되는 측정 매트릭스는 단순해야 합니다. 본 논문에서는 GMW(Gordon-Mills-Welch) 시퀀스를 기반으로 결정론적 측정 행렬을 구성합니다. 제안된 측정 행렬의 열 벡터는 GMW 시퀀스를 순환적으로 이동시켜 생성된다. 일부 최신 측정 행렬과 비교하여 제안된 측정 행렬은 계산 복잡도가 상대적으로 낮고 저장 공간도 덜 필요합니다. 리소스가 제한된 DSN에 적합합니다. 또한, 제안한 측정 행렬은 간단한 쉬프트 레지스터를 이용하여 구현 가능하므로 더욱 실용적이다. 시뮬레이션 결과는 복구 품질 측면에서 제안된 측정 매트릭스가 일부 최신 측정 매트릭스보다 더 나은 성능을 보인다는 것을 보여줍니다.
Haiqiang LIU
China University of Mining and Technology
Gang HUA
China University of Mining and Technology
Hongsheng YIN
China University of Mining and Technology
Aichun ZHU
Nanjing Tech University
Ran CUI
China University of Mining and Technology
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부
Haiqiang LIU, Gang HUA, Hongsheng YIN, Aichun ZHU, Ran CUI, "A Simple Deterministic Measurement Matrix Based on GMW Pseudorandom Sequence" in IEICE TRANSACTIONS on Information,
vol. E102-D, no. 7, pp. 1296-1301, July 2019, doi: 10.1587/transinf.2018EDP7324.
Abstract: Compressed sensing is an effective compression algorithm. It is widely used to measure signals in distributed sensor networks (DSNs). Considering the limited resources of DSNs, the measurement matrices used in DSNs must be simple. In this paper, we construct a deterministic measurement matrix based on Gordon-Mills-Welch (GMW) sequence. The column vectors of the proposed measurement matrix are generated by cyclically shifting a GMW sequence. Compared with some state-of-the-art measurement matrices, the proposed measurement matrix has relative lower computational complexity and needs less storage space. It is suitable for resource-constrained DSNs. Moreover, because the proposed measurement matrix can be realized by using simple shift register, it is more practical. The simulation result shows that, in terms of recovery quality, the proposed measurement matrix performs better than some state-of-the-art measurement matrices.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2018EDP7324/_p
부
@ARTICLE{e102-d_7_1296,
author={Haiqiang LIU, Gang HUA, Hongsheng YIN, Aichun ZHU, Ran CUI, },
journal={IEICE TRANSACTIONS on Information},
title={A Simple Deterministic Measurement Matrix Based on GMW Pseudorandom Sequence},
year={2019},
volume={E102-D},
number={7},
pages={1296-1301},
abstract={Compressed sensing is an effective compression algorithm. It is widely used to measure signals in distributed sensor networks (DSNs). Considering the limited resources of DSNs, the measurement matrices used in DSNs must be simple. In this paper, we construct a deterministic measurement matrix based on Gordon-Mills-Welch (GMW) sequence. The column vectors of the proposed measurement matrix are generated by cyclically shifting a GMW sequence. Compared with some state-of-the-art measurement matrices, the proposed measurement matrix has relative lower computational complexity and needs less storage space. It is suitable for resource-constrained DSNs. Moreover, because the proposed measurement matrix can be realized by using simple shift register, it is more practical. The simulation result shows that, in terms of recovery quality, the proposed measurement matrix performs better than some state-of-the-art measurement matrices.},
keywords={},
doi={10.1587/transinf.2018EDP7324},
ISSN={1745-1361},
month={July},}
부
TY - JOUR
TI - A Simple Deterministic Measurement Matrix Based on GMW Pseudorandom Sequence
T2 - IEICE TRANSACTIONS on Information
SP - 1296
EP - 1301
AU - Haiqiang LIU
AU - Gang HUA
AU - Hongsheng YIN
AU - Aichun ZHU
AU - Ran CUI
PY - 2019
DO - 10.1587/transinf.2018EDP7324
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E102-D
IS - 7
JA - IEICE TRANSACTIONS on Information
Y1 - July 2019
AB - Compressed sensing is an effective compression algorithm. It is widely used to measure signals in distributed sensor networks (DSNs). Considering the limited resources of DSNs, the measurement matrices used in DSNs must be simple. In this paper, we construct a deterministic measurement matrix based on Gordon-Mills-Welch (GMW) sequence. The column vectors of the proposed measurement matrix are generated by cyclically shifting a GMW sequence. Compared with some state-of-the-art measurement matrices, the proposed measurement matrix has relative lower computational complexity and needs less storage space. It is suitable for resource-constrained DSNs. Moreover, because the proposed measurement matrix can be realized by using simple shift register, it is more practical. The simulation result shows that, in terms of recovery quality, the proposed measurement matrix performs better than some state-of-the-art measurement matrices.
ER -