A study on local sensor fusion of wireless sensor networks based on the Neural Network

被引：2
|
作者：
Xu, Xiao-Liang [1 ]
Qiu, Jun-Na [1 ]
Chen, Chun [2 ]
机构：
[1] Hangzhou Dianzi Univ, Sch Comp Sci & Software Engn, Hangzhou 310018, Peoples R China
[2] Zhejiang Univ, Coll Comp Sci, Hangzhou 310027, Peoples R China
来源：
PROCEEDINGS OF 2008 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7 | 2008年
关键词：
local sensor fusion; neural network; BP; RBF; CMAC;
D O I：
10.1109/ICMLC.2008.4621110
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
Taken as the whole network's information fusion, local sensor fusion, integrating signals from different sources and processing locally, is the first step work. Due to the output of sensor nodes is vulnerable to the impact of around environmental factors, such as temperature, humidity, noise, etc., and in order to solve nonlinear problems between input and output, a sensor output compensation model based on the Neural Network is proposed. As the same time, the theory of the Neural Network is outlined, mainly an introduction is made to typical fusion algorithms, along with analyses and comparisons, in three Feed-Forward neural networks, BP, RRF and CMAC, respectively.
引用
收藏
页码：4045 / +
页数：3
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