指挥控制与仿真2016，Vol.38Issue(2)：60-65,6.DOI:10.3969/j.issn.1673-3819.2016.02.013
基于不同能量值特征优选的水声目标识别
Underwater Acoustic Target Recognition Based on Feature Selection of Different Energy Feature
常国勇 1袁富宇 1崔杰1
作者信息
- 1. 江苏自动化研究所，江苏 连云港 222061
- 折叠
摘要
Abstract
Bartlet average periodogram, wavelet transform and empirical mode decomposition method were used to extract the signal�s frequency band energy and intrinsic mode function energy feature, the feature selection of IMF energy is the key point. Then it designs the BP neural network classifier for testing the radiated noise signals of four kinds of skip targets, and gets a good recognition effect.关键词
小波变换/经验模态分解/特征优选/BP神经网络分类器Key words
wavelet transform/empirical mode decomposition/feature selection/BP neural network classifier分类
信息技术与安全科学引用本文复制引用
常国勇,袁富宇,崔杰..基于不同能量值特征优选的水声目标识别[J].指挥控制与仿真,2016,38(2):60-65,6.
