摘要
首先分析希尔伯特-黄变换的实现流程;然后针对流程中的经验模态分解进行阐述,得到原始信号的希尔伯特频谱;最后将希尔伯特-黄变换应用于船舶声信号提取中,并利用最近邻分类法进行分类。实验结果表明,希尔伯特-黄变换能够自适应局部的变化,且分辨率高,能够有效的提取非线性、非平稳的船舶声信号特征。
Firstly,this paper analyzed the implementation process of Hilbert Huang transform. And then the empirical mode decomposition in the process was described in detail. At the same the Hilbert spectrum of the original signal was obtained. Finally,the Hilbert Huang transform was applied to the acoustic signal extraction of ship. Use the nearest neighbor classification method to classify feature. The experimental results showed that the Hilbert Huang transform could adapt to local changes, and the resolution is high,which could effectively extract the characteristics of nonlinear and non-stationary ship acoustic signals.
出处
《舰船科学技术》
北大核心
2016年第11X期91-93,共3页
Ship Science and Technology
关键词
希尔伯特-黄变换
声信号提取
最近邻分类
hilbert huang transform
acoustic signal extraction
nearest neighbor classifier
