Recognition of Fission Signals Based on Wavelet Analysis and Neural Network
Abstract: Because of the
particularity of the uranium components, the nondestructive measuring technique
is needed to detect the radioactivity of the component in certain container and
identify their property to recognize all kinds of uranium components. This
paper establishes a set of samples with the same shape, different weight and
abundance of uranium by simulation. Secondly the cross-correlation function of
timerelation signal between the source detector and the detector could be
calculated. Lastly the result of crosscorrelation functions is through
micro-wavelet analysis to obtain feature vector which is related to the quality
and abundance property of target uranium components. This vector is used to
train neural network and help to identify the quality and abundance of unknown
uranium components.
Author: Li Li, Liu Keqi, Hu
Gen
Journal Code: jptkomputergg160299
Artikel Terkait :
Jp Teknik Komputer gg 2016
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