IEICE TRANSACTIONS on Information
Affinity Propagation Algorithm Based Multi-Source Localization Method for Binary Detection
Summary :
Wireless sensor network (WSN) has attracted many researchers to investigate it in recent years. It can be widely used in the areas of surveillances, health care and agriculture. The location information is very important for WSN applications such as geographic routing, data fusion and tracking. So the localization technology is one of the key technologies for WSN. Since the computational complexity of the traditional source localization is high, the localization method can not be used in the sensor node. In this paper, we firstly introduce the Neyman-Pearson criterion based detection model. This model considers the effect of false alarm and missing alarm rate, so it is more realistic than the binary and probability model. An affinity propagation algorithm based localization method is proposed. Simulation results show that the proposed method provides high localization accuracy.
- Publication
- IEICE TRANSACTIONS on Information Vol.E100-D No.8 pp.1916-1919
- Publication Date
- 2017/08/01
- Publicized
- 2017/05/10
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.2016EDL8235
- Type of Manuscript
- LETTER
- Category
- Information Network
Authors
Yan WANG
Northeastern University
Long CHENG
Northeastern University
Jian ZHANG
Nanjing University of Information Science and Technology
Keyword
Latest Issue
Copyrights notice of machine-translated contents
The copyright of the original papers published on this site belongs to IEICE. Unauthorized use of the original or translated papers is prohibited. See IEICE Provisions on Copyright for details.
Cite this
Copy
Yan WANG, Long CHENG, Jian ZHANG, "Affinity Propagation Algorithm Based Multi-Source Localization Method for Binary Detection" in IEICE TRANSACTIONS on Information,
vol. E100-D, no. 8, pp. 1916-1919, August 2017, doi: 10.1587/transinf.2016EDL8235.
Abstract: Wireless sensor network (WSN) has attracted many researchers to investigate it in recent years. It can be widely used in the areas of surveillances, health care and agriculture. The location information is very important for WSN applications such as geographic routing, data fusion and tracking. So the localization technology is one of the key technologies for WSN. Since the computational complexity of the traditional source localization is high, the localization method can not be used in the sensor node. In this paper, we firstly introduce the Neyman-Pearson criterion based detection model. This model considers the effect of false alarm and missing alarm rate, so it is more realistic than the binary and probability model. An affinity propagation algorithm based localization method is proposed. Simulation results show that the proposed method provides high localization accuracy.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2016EDL8235/_p
Copy
@ARTICLE{e100-d_8_1916,
author={Yan WANG, Long CHENG, Jian ZHANG, },
journal={IEICE TRANSACTIONS on Information},
title={Affinity Propagation Algorithm Based Multi-Source Localization Method for Binary Detection},
year={2017},
volume={E100-D},
number={8},
pages={1916-1919},
abstract={Wireless sensor network (WSN) has attracted many researchers to investigate it in recent years. It can be widely used in the areas of surveillances, health care and agriculture. The location information is very important for WSN applications such as geographic routing, data fusion and tracking. So the localization technology is one of the key technologies for WSN. Since the computational complexity of the traditional source localization is high, the localization method can not be used in the sensor node. In this paper, we firstly introduce the Neyman-Pearson criterion based detection model. This model considers the effect of false alarm and missing alarm rate, so it is more realistic than the binary and probability model. An affinity propagation algorithm based localization method is proposed. Simulation results show that the proposed method provides high localization accuracy.},
keywords={},
doi={10.1587/transinf.2016EDL8235},
ISSN={1745-1361},
month={August},}
Copy
TY - JOUR
TI - Affinity Propagation Algorithm Based Multi-Source Localization Method for Binary Detection
T2 - IEICE TRANSACTIONS on Information
SP - 1916
EP - 1919
AU - Yan WANG
AU - Long CHENG
AU - Jian ZHANG
PY - 2017
DO - 10.1587/transinf.2016EDL8235
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E100-D
IS - 8
JA - IEICE TRANSACTIONS on Information
Y1 - August 2017
AB - Wireless sensor network (WSN) has attracted many researchers to investigate it in recent years. It can be widely used in the areas of surveillances, health care and agriculture. The location information is very important for WSN applications such as geographic routing, data fusion and tracking. So the localization technology is one of the key technologies for WSN. Since the computational complexity of the traditional source localization is high, the localization method can not be used in the sensor node. In this paper, we firstly introduce the Neyman-Pearson criterion based detection model. This model considers the effect of false alarm and missing alarm rate, so it is more realistic than the binary and probability model. An affinity propagation algorithm based localization method is proposed. Simulation results show that the proposed method provides high localization accuracy.
ER -
English
