DocumentCode :
393534
Title :
Using wavelet transform and neural network for solid velocity profiles
Author :
Wu, Xin-Jie ; Lee, Ju-Jang ; Qin, Gui-He
Author_Institution :
Dept. of Phys., Liaoning Univ., Shenyang, China
Volume :
2
fYear :
2002
fDate :
5-7 Aug. 2002
Firstpage :
1091
Abstract :
A measurement method of velocity profile is presented. The bandwidth of the filtering signal of sensor is difficult to be accurately obtained. To overcome the shortcoming, wavelet transform is used to determine the bandwidth of the filtering signal. RBF neural network is employed to replace conventional image reconstruction algorithms, which has fast and accurate advantages. The simulation experimental results have shown that the velocity measurement method is reliable.
Keywords :
image reconstruction; radial basis function networks; wavelet transforms; RBF neural network; image reconstruction; neural network; solid velocity profiles; velocity profile; wavelet transform; Bandwidth; Capacitance; Correlation; Filtering; Fluid flow measurement; Low pass filters; Neural networks; Solids; Velocity measurement; Wavelet transforms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
SICE 2002. Proceedings of the 41st SICE Annual Conference
Print_ISBN :
0-7803-7631-5
Type :
conf
DOI :
10.1109/SICE.2002.1195331
Filename :
1195331
Link To Document :
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