Research on the Clustering Algorithm of the ClassIncremental Learning Model for Underwater Vehicle Noise Source Recognition

GAO Zhihua1,BEN Kerong1,ZHANG Linke2

doi:10.3969/j.issn.1007130X.2010.

2010 , Vol. 32 >Issue 9: 53 - 56

DOI: https://doi.org/10.3969/j.issn.1007130X.2010.

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Research on the Clustering Algorithm of the ClassIncremental Learning Model for Underwater Vehicle Noise Source Recognition

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(1.Department of Computer Engineering,Naval University of Engineering,Wuhan 430033;
2.Institute of Noise and Vibration,Naval University of Engineering,Wuhan 430033,China)

Received date: 2010-03-16

Revised date: 2010-06-18

Online published: 2010-09-02

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Abstract

The underwater vehicle machinery noise source recognition features that the training samples is limited and have abrupt noise samples. Based on these characteristics,this paper proposes a densitybased algorithm which is parameter adjustable. And this novel algorithm is an important component of the underwater vehicle machinery noise source recognition system with incremental learning ability. The experimental results show the new algorithm can avoid the parameter sensitivity of DBSCAN. Labeled samples by this algorithm can directly be used as the classifier training samples,saving lots of time and system resources.

Key words： noise source recognition;incremental learning;clustering algorithms

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GAO Zhihua1,BEN Kerong1,ZHANG Linke2 . Research on the Clustering Algorithm of the ClassIncremental Learning Model for Underwater Vehicle Noise Source Recognition[J]. Computer Engineering & Science, 2010 , 32(9) : 53 -56 . DOI: 10.3969/j.issn.1007130X.2010.

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