DocumentCode
527449
Title
Multi-sensor information fusion based on BP network
Author
Li, Guoyu
Author_Institution
Sch. of Phys. & Optoelectron. Eng., Dalian Univ. of Technol., Dalian, China
Volume
3
fYear
2010
fDate
10-12 Aug. 2010
Firstpage
1442
Lastpage
1445
Abstract
The output of pressure sensor is affected by non-objection parameters in its application, such as temperature, power fluctuation and so on. Multi-sensor information fusion based on BP network can eliminate the side effect of non-objection parameters and improve the accuracy and reliability for the pressure sensor. This method based on LMBP algorithm of BP network has not only a simple network structure, but also a quick learning rate, showing a better prospect. The paper describes the LMBP algorithm, deduces the matrix formula of the two-layer network, and makes use of LMBP algorithm to fuse the temperature, power fluctuation and pressure information of the pressure sensor. Finally the paper fuses the example data of the pressure sensor with the help of the MATLAB software and draws a conclusion that the LMBP algorithm eliminates easily the affection of the non-objection parameters and improves the accuracy of the pressure sensor.
Keywords
backpropagation; matrix algebra; neural nets; pressure sensors; sensor fusion; BP network; LMBP algorithm; MATLAB software; matrix formula; multisensor information fusion; power fluctuation; pressure sensor; temperature; Accuracy; Artificial neural networks; Equations; Fluctuations; Mathematical model; Temperature sensors; Training; BP network; algorithm; information fusion; pressure sensor;
fLanguage
English
Publisher
ieee
Conference_Titel
Natural Computation (ICNC), 2010 Sixth International Conference on
Conference_Location
Yantai, Shandong
Print_ISBN
978-1-4244-5958-2
Type
conf
DOI
10.1109/ICNC.2010.5582862
Filename
5582862
Link To Document