The Feature Extraction and Classification of Ocean Acoustic Signals Based on Wave Structure

蔡悦斌; 张明之; 史习智; 林良骥

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The Feature Extraction and Classification of Ocean Acoustic Signals Based on Wave Structure

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- The Feature Extraction and Classification of Ocean Acoustic Signals Based on Wave Structure
- Acta Electronica Sinica Issue 6, Pages: 129-130(1999)
- 作者机构：
  
  1.   上海交通大学!上海
  2.   200030
  3.   大连760研究所!大连
  4.   116013
- 作者简介：
- 基金信息：
- DOI：
  CLC： TN911.4
- Published：1999
- 稿件说明：
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[1]蔡悦斌,张明之,史习智,林良骥.舰船噪声波形结构特征提取及分类研究[J].电子学报,1999(06):129-130.

蔡悦斌, 张明之, 史习智, et al. The Feature Extraction and Classification of Ocean Acoustic Signals Based on Wave Structure[J]. Acta Electronica Sinica, 1999, (6): 129-130.
[1]蔡悦斌,张明之,史习智,林良骥.舰船噪声波形结构特征提取及分类研究[J].电子学报,1999(06):129-130. DOI：

蔡悦斌, 张明之, 史习智, et al. The Feature Extraction and Classification of Ocean Acoustic Signals Based on Wave Structure[J]. Acta Electronica Sinica, 1999, (6): 129-130. DOI：

摘要

本文系统深入地分析研究了舰船噪声信号的时域波形结构特征，利用舰船噪声信号的过零点、峰间幅值、波长差、波列面积分布以及时域特性提取技术，将原始舰船噪声信号时域波形分类信息表达成了11维的分类特征向量，同时设计了结构自适应模型聚类神经网络分类器，对提取的舰船噪声分类特征向量进行分类．训练样本集平均识别率达96．72％；测试样本集平均识别率达88．39％，分类实验结果令人满意

Abstract

The method of the feature vector extraction of ocean acoustics signals based on the wave structure is presented. Then the structurally adaptive fuzzy-clustering neural network model is applied to design a new classifier for the ocean acoustics signals. The result shows that the presented method of feature vector extraction of ocean acoustics signals and the designed classifier are satisfactory.

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