A Neural Data Fusion Algorithm in Wireless Sensor Network

Author

Feng, Xiufang ; Xu, Zhanwei

Author_Institution

Coll. of Comput. & Sci., Taiyuan Univ. of Technol., Taiyuan, China

fYear

2009

fDate

16-17 May 2009

Firstpage

54

Lastpage

57

Abstract

Data fusion technology is widely utilized in energy constraint wireless sensor network (WSN) to reduce the amount of messages exchanged between sensor nodes. However, there are many similarities between wireless sensor network and artificial neural network. In this paper we present a neural data fusion algorithm based on PCA to classify the states of environment. The results attained by experiments show that the algorithm proposed in this paper can reduce the data transmission in WSN effectively and implement classification of different types of parameters simply and practicably.

Keywords

neural nets; principal component analysis; sensor fusion; wireless sensor networks; PCA; artificial neural network; energy constraint wireless sensor network; neural data fusion algorithm; principal component analysis; Clustering algorithms; Covariance matrix; Educational institutions; Mechanical sensors; Neural networks; Principal component analysis; Sensor fusion; Sensor systems; Vectors; Wireless sensor networks; PCA neural network; data fusion; wireless sensor network (WSN);

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits, Communications and Systems, 2009. PACCS '09. Pacific-Asia Conference on

Conference_Location

Chengdu

Print_ISBN

978-0-7695-3614-9

Type

conf

DOI

10.1109/PACCS.2009.115

Filename

5232285