An improved incremental least-mean-squares algorithm for distributed estimation over wireless sensor networks
An improved incremental least-mean-squares algorithm for distributed estimation over wireless sensor networks
复制标题
无线传感器网络分布式估计的改进增量最小均方算法
DOI：
10.1177/1550147717703967
复制
发表时间：
2017-04
影响因子：
2.3
通讯作者：
Wan Runze
中科院分区：
文献类型：
--
作者：
Wu Mou;Tan Liansheng;Yang Rong;Wan Runze
分布式参数估计问题因其在无线传感器网络中某些应用的重要基础而备受关注。在这项工作中，我们首先从初始收敛率、稳态收敛行为和振荡等方面研究了现有增量最小均方算法和传统最速下降算法之间的性能权衡，并提出了改进的动机。由此，我们提出了一种改进的增量最小均方分布式估计算法，该算法从增量最小均方算法出发，以提高初始收敛速度和稳态性能为目标。所提出的算法满足无线传感器网络递减步长的要求，而不会增加任何通信开销，并且推导了平均稳定性条件作为实际指南。使用无线传感器网络中的目标定位模型来说明该算法的效果。仿真结果证实了我们的方法的性能改进以及在无线传感器网络中应用的有效性。
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 algorithm that starts from the incremental least-mean-squares algorithm and works toward the objective of improvement on initial convergence rate and steady-state performance. The proposed algorithm meets the requirements of diminishing step size for wireless sensor networks without any increase in communication overhead and the mean stability condition is derived for a practical guideline. A target localization model in wireless sensor networks is used to illustrate the effect of the proposed algorithm. Simulation results confirm the performance improvement of our method, as well as the effectiveness of application in wireless sensor networks.
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DOI：
10.1145/2629667
发表时间：
2014-12
期刊：
ACM Transactions on Sensor Networks (TOSN)
影响因子：
--
作者：
T. Panigrahi;G. Panda;B. Mulgrew
通讯作者：
T. Panigrahi;G. Panda;B. Mulgrew
DOI：
10.1109/iccsp.2015.7322822
发表时间：
2015-04
期刊：
2015 International Conference on Communications and Signal Processing (ICCSP)
影响因子：
--
作者：
M. Sowjanya;A. Sahoo;Sananda Kumar
通讯作者：
M. Sowjanya;A. Sahoo;Sananda Kumar
能量受限无线传感器网络上基于共识的分布式估计的传感器选择方案
影响因子：
6
作者：
Wen, Yang(杨文);Hongbo, Shi
通讯作者：
Hongbo, Shi
DOI：
10.1109/icassp.2013.6638751
发表时间：
2013-05
期刊：
2013 IEEE International Conference on Acoustics, Speech and Signal Processing
影响因子：
--
作者：
W. B. Lopes;C. G. Lopes
通讯作者：
W. B. Lopes;C. G. Lopes
影响因子：
4.4
作者：
Dogançay, K;Hashemi-Sakhtsari, A
通讯作者：
Hashemi-Sakhtsari, A