DocumentCode :
2339889
Title :
Application of neural network data fusion algorithm in measurement circuit
Author :
Ni, Xiaoyong ; Wang, Dianhong ; Zhang, Hongjian
Author_Institution :
Sch. of Mech. & Electron., China Univ. of Geosci., Wuhan
fYear :
2008
fDate :
3-5 June 2008
Firstpage :
12
Lastpage :
17
Abstract :
Multi-sensor data fusion is a technology to fuse data from multiple sensors in order to make a more accurate estimation of the environment through measurement and detection. In this article a smart measurement circuit which embeds with neural network data fusion algorithm is designed with FPGA-based system-on-chip (SoC) architecture. The circuit can operate in power down mode and its parameters are adjusted on-line. Influence of structure parameters to the network performance are analyzed and a partition succeed method is presented to shorten the time of network training on-line.
Keywords :
field programmable gate arrays; neural nets; sensor fusion; system-on-chip; FPGA; SoC; measurement circuit; multisensor data fusion; neural network data fusion algorithm; partition succeed method; system-on-chip; Algorithm design and analysis; Circuits; Detectors; Field programmable gate arrays; Fires; Fuses; Mechanical variables measurement; Multi-layer neural network; Neural networks; Sensor fusion;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Electronics and Applications, 2008. ICIEA 2008. 3rd IEEE Conference on
Conference_Location :
Singapore
Print_ISBN :
978-1-4244-1717-9
Electronic_ISBN :
978-1-4244-1718-6
Type :
conf
DOI :
10.1109/ICIEA.2008.4582471
Filename :
4582471
Link To Document :
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