[1]聂伟荣,朱继南,赵玉霞.基于改进BP网络的地震动信号目标识别[J].南京理工大学学报(自然科学版),2000,(01):20-23.
 NieWeirong ZhuJinan ZhaoYuxia.Microseismic Signal Targets Identification Based on Improved BP Neural Networks[J].Journal of Nanjing University of Science and Technology,2000,(01):20-23.
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基于改进BP网络的地震动信号目标识别()
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《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

卷:
期数:
2000年01期
页码:
20-23
栏目:
出版日期:
2000-02-28

文章信息/Info

Title:
Microseismic Signal Targets Identification Based on Improved BP Neural Networks
作者:
聂伟荣朱继南赵玉霞
南京理工大学机械学院, 南京210094
Author(s):
NieWeirong ZhuJinan ZhaoYuxia
School of Mechanics,NUST, Nanjing 210094
关键词:
神经网络 模式识别 小波变换 地震动信号 小波包
Keywords:
neural networks pat tern recognit ion wavelet s transform seismic sig nalsw avelet s package
分类号:
P315
摘要:
应用人工神经网络进行目标识别是当前模式识别的重要方法之一。前向多层神经网络及其BP算法是发展较为成熟的一种。该文对BP算法加以改进 ,使得其性能有所提高 ,收敛速度加快。针对战场监视传感器系统中处于一级警戒的地震动传感器 ,对在良好土质地面实测的人员脚步、汽车、坦克的地震动信号进行分析 ,利用小波变换和小波包分解提取能量特征 ,采用两级级连网络进行目标识别 ,识别率在 94.5 %以上
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.

参考文献/References:

1 徐佩霞, 孙功宪. 小波分析与应用实例. 合肥: 中国科学技术出版社. 1996
2 黄得双. 神经网络模式识别系统理论. 北京: 电子工业出版社. 1996
3 郁文贤. 军事电子信息处理中的人工神经网络技术. 国防科技大学学报, 1998, 20( 3) : 92~ 98
4 赵玉霞. 多传感器监视系统的目标识别: [ 硕士学位论文] . 南京: 南京理工大学, 1999

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备注/Memo

备注/Memo:
聂伟荣 女 30 岁 博士生
更新日期/Last Update: 2013-03-25