An algorithm of data fusion using neural network

Author

Zhao, Xianhong ; Wang, Jinchan

Author_Institution

Sch. of Electron. & Inf. Eng., Henan Univ. of Sci. & Technol., Luoyang, China

fYear

2011

fDate

15-17 April 2011

Firstpage

2950

Lastpage

2953

Abstract

Data fusion is meanly used in data integration and data processing. In this paper, an object-oriented algorithm of data fusion is presented. Firstly, neural network theory was employed in the identification and location fixing of target in a certain area at discrete time. Then an experimental model was setup. In the given model, adaptive resonance theory of neural network was adopted and a double-layer self-organized neural network was established. This provided a new method to implement neural network using data fusion algorithm.

Keywords

ART neural nets; object-oriented methods; self-organising feature maps; sensor fusion; adaptive resonance theory; data fusion; data integration; data processing; discrete time; double-layer self-organized neural network; neural network theory; object-oriented algorithm; target identification; target location; Adaptation model; Artificial neural networks; Conferences; Global Positioning System; Informatics; Object oriented modeling; data fusion; neural network; self-organization;

fLanguage

English

Publisher

ieee

Conference_Titel

Electric Information and Control Engineering (ICEICE), 2011 International Conference on

Conference_Location

Wuhan

Print_ISBN

978-1-4244-8036-4

Type

conf

DOI

10.1109/ICEICE.2011.5778315

Filename

5778315