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An improved incremental least-mean-squares algorithm for distributed estimation over wireless sensor networks

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成果类型:
期刊论文
作者:
Wu, Mou*;Tan, Liansheng(谭连生);Yang, Rong;Wan, Runze
通讯作者:
Wu, Mou
作者机构:
[Wu, Mou; Yang, Rong] Hubei Univ Sci & Technol, Sch Comp Sci & Technol, Xianning 437100, Peoples R China.
[Tan, Liansheng] Cent China Normal Univ, Sch Comp Sci, Wuhan, Peoples R China.
[Wan, Runze] Hubei Univ Educ, Sch Comp, Wuhan, Peoples R China.
通讯机构:
[Wu, Mou] H
Hubei Univ Sci & Technol, Sch Comp Sci & Technol, Xianning 437100, Peoples R China.
语种:
英文
关键词:
Distributed estimation;incremental least mean squares;steepest descent;wireless sensor networks;target localization
期刊:
International Journal of Distributed Sensor Networks
ISSN:
1550-1477
年:
2017
卷:
13
期:
4
页码:
155014771770396
基金类别:
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The work described in this paper was supported by the Doctor Initial Funding of Hubei University of Science and Technology (nos BK1520 and BK1521), the National Natural Science Foundation of China (nos 61370107 and 61672258), the Project of Natural Science Foundation of Hubei Province (no. 2015CFB405), and the Hubei Provincial Department of Education Scientific Research Programs for Youth Project (no. Q20153003).
机构署名:
本校为其他机构
院系归属:
计算机学院
摘要:
Distributed parameter estimation problem has attracted much attention due to its important foundation of some applications in wireless sensor networks. In this work, we first investigate the performance tradeoff between existing incremental least-mean-squares algorithm and traditional steepest-descent algorithm from the aspects of initial convergence rate, steady-state convergence behavior, and oscillation, and present the motivations for improvements. Thereby we propose an improved incremental least-mean-squares distributed estimation algorith...

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