删除或更新信息，请邮件至freekaoyan#163.com(#换成@)

水下声目标的梅尔倒谱系数智能分类方法

本站小编 Free考研考试/2022-01-02
-->
张少康,田德艳.水下声目标的梅尔倒谱系数智能分类方法[J].,2019,38(2):267-272
水下声目标的梅尔倒谱系数智能分类方法
Intelligent classification method of Mel frequency cepstrum coefficient for underwater acoustic targets
投稿时间：2018-09-05修订日期：2019-03-01
中文摘要:
传统水下声目标识别分类方法具有较强的人机交互特性，无法满足未来水下无人平台智能识别分类水声目标的需求。针对这一问题，提出了一种基于梅尔倒谱系数（MFCC）的水下声目标智能识别分类方法，该方法通过提取水下声目标梅尔倒谱系数特征，采用长短时记忆网络（LSTM）构建了智能识别分类模型。使用实际水声信号对该方法进行了验证，结果表明，基于梅尔倒谱系数的水下声目标智能识别分类方法能够在不依赖人工提取特征的情况下，对目标噪声进行识别分类，具备智能化识别分类能力。
英文摘要:
The traditional methods of underwater target noise recognition have strong human-computer interaction characteristics, which can not meet the requirements of intelligent underwater acoustic target recognition for the future unmanned underwater platform. To solve this problem, an intelligent recognition method of underwater target noise based on Mel Cepstrum coefficient (MFCC) is proposed. By extracting the features of Mel Cepstrum coefficient, an intelligent recognition model is constructed by using long short-term memory network (LSTM). The underwater acoustic signal is used to verify the method. The results show that the method of underwater target noise intelligent recognition based on Mel cepstrum coefficient can identify the target noise without relying on the artificial feature extraction and have an intelligent recognition ability.
DOI：10.11684/j.issn.1000-310X.2019.02.017
中文关键词:水下声目标识别分类，梅尔倒谱系数，长短时记忆网络，智能分类
英文关键词:Underwater acoustic targets classification, Mel cepstrum, Long short-term memory network, Intelligent classification
基金项目:
作者单位E-mail
张少康海军潜艇学院darth_zhang@163.com
田德艳青岛海洋科学与技术国家实验室darth_zhang@163.com
摘要点击次数:1137
全文下载次数:865
查看全文查看/发表评论下载PDF阅读器
相关附件：保密证明修改说明1修改说明1论文图附件1
关闭








PDF全文下载地址:

http://yysx.cnjournals.cn/ch/reader/create_pdf.aspx?file_no=18124&flag=1&journal_id=yysx&year_id=2019
相关话题/智能 海军潜艇学院 中文 网络 实验室

Free考研考试FreeKaoYan.Com
欢迎来到Free考研考试，"为实现人生的Free而奋斗"

© 2020 FreeKaoYan! . All rights reserved.