舰船电子工程2019，Vol.39Issue(2)：149-153,166,6.DOI:10.3969/j.issn.1672-9730.2019.02.038
基于卷积神经网络的水声目标分类技术
Underwater Acoustic Targets Classification Based on Convolutional Neural Networks
摘要
Abstract
This paper introduces the convolutional neural networks method and it's computing process,with the characteris?tics of convolutional neural networks,the deep learning algorithm applied in underwater acoustic targets classification is raised. With the simulation experiment of convolutional neural networks method,the ships,the ambient sea noise,the merchant ships and the fishing-boat are classified. With the comparison of classic underwater acoustic targets classification methods,the identification performance of convolutional neural networks method turns out to be better.关键词
卷积神经网络/深度学习/水声目标分类Key words
convolutional neural networks/deep learning/underwater acoustic targets classification分类
信息技术与安全科学引用本文复制引用
吕海涛,巩健文,孔晓鹏..基于卷积神经网络的水声目标分类技术[J].舰船电子工程,2019,39(2):149-153,166,6.基金项目
山东省重点研发计划(编号:2016CYJS02A01)资助. （编号:2016CYJS02A01）
