Study on ship target classification based on Mel-cepstrum and BP neural networks

WANG Yi-chuan; LI Zhi-zhong

doi:10.13873/j.1000-97872011.06.004

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Study on ship target classification based on Mel-cepstrum and BP neural networks

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- Study on ship target classification based on Mel-cepstrum and BP neural networks
- Vol. 30, Issue 6, Pages: 55-57+67(2011)
- 作者机构：
  
  海军潜艇学院航海观通系
- 作者简介：
- 基金信息：
- DOI：10.13873/j.1000-97872011.06.004
  CLC： TB533.2;TP183;U661.4
- Published：2011
- 稿件说明：
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[1]王易川,李智忠.基于Mel倒谱和BP神经网络的船舶目标分类研究[J].传感器与微系统,2011,30(06):55-57+67.

WANG Yi-chuan, LI Zhi-zhong. Study on ship target classification based on Mel-cepstrum and BP neural networks[J]. 2011, 30(6): 55-57+67.
[1]王易川,李智忠.基于Mel倒谱和BP神经网络的船舶目标分类研究[J].传感器与微系统,2011,30(06):55-57+67. DOI： 10.13873/j.1000-97872011.06.004.

WANG Yi-chuan, LI Zhi-zhong. Study on ship target classification based on Mel-cepstrum and BP neural networks[J]. 2011, 30(6): 55-57+67. DOI： 10.13873/j.1000-97872011.06.004.

摘要

Mel倒谱系数分析依据人耳听觉特性

可以提取有利于船舶目标分类的特征。前向神经网络的反向传播算法对类别数目小但分类困难的模式识别问题有良好的分类效果。针对Mel倒谱系数分析提取的船舶目标分类识别特征

采用前向神经网络的反向传播算法

可以有效对船舶目标进行分类。

Abstract

Mel-cepstrum analysis based on characteristics of human hearing is able to extract feature for ship target classification.Back-propagation algorithms of forward neural network is suitable for pattern recognition problem when the number of classes is small but classification is difficult.Aimed at ship targets features are extracted by Mel-cepstrum analysis

using back-propagation algorithms of forward neural network

ship targets are classificated.

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Keywords

references

基于MFCC和LPCC的说话人识别 [J]. 余建潮,张瑞林. 计算机工程与设计 . 2009(05)

语音信号处理[M]. 机械工业出版社 , 赵力编著, 2003

模式识别[M]. 哈尔滨工程大学出版社 , 黄凤岗,宋克欧编著, 1998

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