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支持向量机的水声信号分类识别

Ship Electronic Engineering(2008)

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Abstract
研究水声信号识别特征的提取,在此基础上采用支持向量机理论,提出了一种水声信号的分类识别算法。该算法选取两类水声信号,提取它们的混沌特征值关联维数和h2熵作为目标信息,每类信号各提取32组数据,取两类水声信号各8组数据作为训练样本,训练支持向量机,其它样本用于验证。结果表明,支持向量机的分类算法能实现对目标的有效分类,分类效果较好,比较适合小样本、非线性分类。
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Key words
support vector machine,classification and recognition,chaotic characteristic parameter,underwater acoustic signal
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