[1]杨期鹤,栗华.被动声纳信号分类特征提取的研究[J].东南大学学报(自然科学版),1999,29(6):16-20.[doi:10.3969/j.issn.1001-0505.1999.06.004]
 Yang Qihe,Li Hua.Feature Extraction for Passive Sonar Signal Classfication[J].Journal of Southeast University (Natural Science Edition),1999,29(6):16-20.[doi:10.3969/j.issn.1001-0505.1999.06.004]
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被动声纳信号分类特征提取的研究()
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《东南大学学报(自然科学版)》[ISSN:1001-0505/CN:32-1178/N]

卷:
29
期数:
1999年第6期
页码:
16-20
栏目:
数学、物理学、力学
出版日期:
2000-11-20

文章信息/Info

Title:
Feature Extraction for Passive Sonar Signal Classfication
作者:
杨期鹤 栗华
东南大学无线电工程系,南京 210096
Author(s):
Yang Qihe Li Hua
Department of Radio Engineering, Southeast University, Nanjing 210096
关键词:
被动声纳信号分类 特征提取 谱估计 小波变换 语音识别 人工神经网络
Keywords:
passive sonar signal classification feature extraction spectrum estimation wavelet transform speech identification artificial neural network
分类号:
O235
DOI:
10.3969/j.issn.1001-0505.1999.06.004
摘要:
对被动声纳信号进行了分析和特征提取,基于听觉系统识别声音信号的原理,提出了一种新颖的平稳恒Q特征,并给出了距离指数和识别指数2种更为合理的评价方法。实验结果表明本文提出的平稳恒Q特征较原有几种典型特征,具有良好的分类正确性.
Abstract:
An analysis of passive sonar signal and extraction of their features is described.By researching the principle of hearing system in identification of sound signal, a new steady constant Q feature is proposed. Two more reasonable evaluation methods of distance and identification index are given. Results of the experiment show that the steady constant Q feature method has higher correct classification rate.

参考文献/References:

[1] 何振亚.数字信号处理的理论与应用.北京:人民邮电出版社,1983.167~288
[2] 王宏禹.现代谱估计.南京:东南大学出版社,1990.16~127
[3] Yang X W,Wang K,Shamma S A.Auditory representantion of acoustic signals.IEEE Trans IT,1992,38(2):824~839

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备注/Memo

备注/Memo:
第一作者:男,1941年生,副教授.
更新日期/Last Update: 1999-11-20