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Microseismic Signal Targets Identification Based on Improved BP Neural Networks(PDF)

《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

Issue:
2000年01期
Page:
20-23
Research Field:
Publishing date:

Info

Title:
Microseismic Signal Targets Identification Based on Improved BP Neural Networks
Author(s):
NieWeirong ZhuJinan ZhaoYuxia
School of Mechanics,NUST, Nanjing 210094
Keywords:
neural networks pat tern recognit ion wavelet s transform seismic sig nalsw avelet s package
PACS:
P315
DOI:
-
Abstract:
It is one of the important methods of pat tern recognit ion to apply neural netw orks to target classificat ion. Forw ard propagat ion mult-i layers neural networks and it s BP a-l gorithm are used w idely . In this art icle, some measures are taken to improve BP algorithm, and to make its performance bet ter and it s convergence speed quicker. The seismic sensor is an essential sensor in bat tlefield w atching system. By test ing, a g reat number of seismic sig nals are obtained on footsteps, w heeled-vehicle and tank. These signals are processed using w avelets transform and w avelets package. The energy spectrum features of these signals are ex tracted, and tw o series connected BP neural networks ident ify them. The results of 94. 5% proper ident ification are at tained.

References:

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Memo

Memo:
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Last Update: 2013-03-25