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基于小波变换和支持向量机的光谱多组分分析 被引量:13

Spectral Multicomponent Analysis Based on Wavelet Transform and Support Vector Machine
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摘要 以符合朗伯—比尔定律的光谱信号为研究对象,在运用小波变换对光谱信号进行去除噪声处理的基础上,建立了基于支持向量机的多组分分析模型,最后采用计算机模拟的方式对该方法进行了举例说明.实例表明,该方法能较好地解决非线性、小样本条件下的多组分分析问题. This paper took spectral signal according with Lambert-beer law as object, and introduced basic method of denoise with wavelet transform, and researched and established model of spectral multicomponent analysis based on support vector machine. Then computer simulation method gave an example to explain in the end, the example indicated that the method based on support vector machine can preferably solve the question of nonlinearity, small-sample in the spectral multicomponent analysis.
出处 《光子学报》 EI CAS CSCD 北大核心 2005年第10期1514-1517,共4页 Acta Photonica Sinica
基金 国家自然科学基金重点项目(69476023) 科技部国际合作项目(2004DFA00600) 国家863计划(2004AA4040 2004AA404023) 重庆市科委(CSTC 2005CF2002)资助项目
关键词 光谱分析 小波变换 支持向量机 Spectral analysis ~ Wavelet transform ~ Support vector machine
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