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Alternative Titlefusion algorithm of hierarchical data in cluster for wireless sensor network
李海永; 李晓; 张岩
Source Publication计算机工程


Other Abstract

In order to adapt to resources-constrained Wireless Sensor Network(WSN),an improved Fusion Algorithm of Hierarchical Data in Cluster for WSN is proposed on the basis of the Principal Component Analysis(PCA).Self-learning weighted method estimates measured variance of every sensor.The linear unbiased minimum variance estimate method is adopted,which is able to reduce the errors of measured datum of the cluster sensor nodes.The formulas of comprehensive support degree of each sensor and data fusion are obtained according to the PCA method.The application example and simulation results prove that the method is effective and reliable.

Keyword无线传感器网络 数据融合 线性估计 主成分分析
Subject AreaComputer Science (Provided By Thomson Reuters)
Indexed ByCSCD
Citation statistics
Cited Times:1[CSCD]   [CSCD Record]
Document Type期刊论文
Recommended Citation
GB/T 7714
李海永,李晓,张岩. 无线传感器网络簇内分级数据融合算法[J]. 计算机工程,2011,37(12):82-84.
APA 李海永,李晓,&张岩.(2011).无线传感器网络簇内分级数据融合算法.计算机工程,37(12),82-84.
MLA 李海永,et al."无线传感器网络簇内分级数据融合算法".计算机工程 37.12(2011):82-84.
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