运用RBF径向基神经网络识别基于小波变换的淫羊藿苷红外光谱指纹特征  

Identifying the Characteristics of FTIR Spectra of Herba Epimedii Icariin via Wavelet Analysis and RBF Neural Network

作　　者：张晓明[1] 周群[2] 郭宝林[3] 孙素琴[2] 

机构地区：[1]香港浸会大学计算机科学系 [2]清华大学化学系生命有机磷化学及化学生物学教育部重点实验室,北京100084 [3]中国医学科学院中国协和医科大学药用植物研究所,北京100094

出　　处：《光谱学与光谱分析》2009年第7期1830-1834,共5页Spectroscopy and Spectral Analysis

基　　金：香港研究資助局项目(HKBU210306);国家自然科学基金项目(30270101)资助

摘　　要：运用RBF径向基神经网络对基于傅里叶变换红外光谱(FTIR)法、相关系数比对法及多层次小波变换所提取的淫羊藿药材样本有效成分指纹特征进行识别。样品包括药典选用的5个物种(淫羊藿Epimedium brevicornu Maxim.、箭叶淫羊藿E.sagittatum(Sieb.et Zucc.)Maxim.、柔毛淫羊藿E.pubescens Maxim.、朝鲜淫羊藿E.koreanum Nakai和巫山淫羊藿E.wushanense T.S.Ying)和其他物种共计250个样本。淫羊藿指标成分淫羊藿苷在原药材和甲醇提取物的红外光谱图上,具有较明显的1 259 cm-1特征峰,经典的HPLC法的定量分析结果也佐证了淫羊藿苷的含量与1 259 cm-1峰的位置具有很好的一致性。为此该峰可以用来作为判别各物种淫羊藿药材是否含有淫羊藿苷的重要依据。在此基础上,采用相关系数比对法和多层次的小波变换法消除了因淫羊藿苷含量低、吸收峰弱,信号和噪声大的问题,增强了RBF径向基神经网络的识别效果。初步建立了基于小波变换和RBF径向基神经网络淫羊藿原药材红外光谱快速识别淫羊藿苷指标成分的一种新方法。In the present paper, the authors extracted active components of herba epimedii and their important features using Fourier transform infrared spectroscopy （FTIR）, correlation coefficient comparison, and multilevel wavelet analysis. The extracted features were then used to classify herba epimedii via radial basis function （RBF） neural network. There were altogether 250 samples of the medicine with various different types, including epimedium brevicornu Maxim, E. sagittatum （Sieb. et Zucc. ） Maxim, E. pubescens Maxim. , E. koreanum Nakai and Ewushanense T. S. Ying. An important component of herba epimedii, herba epimedii ieariin, has a special peak at 1 259 cm^-1 on the FTIR spectra obtained from the methanol extraction, which is consistent with the result obtained by traditional HPLC qualitative analysis. Therefore, this special peak can be used to determine if herba epimedii contains herba cpimedii icariin. Furthermore, large variations in the spectrum caused by low content of icariin, weak absorption peaks and noise were successfully removed by applying correlation coefficient comparison and multilevel wavelet analysis, which significantly increased the quality of classification of RBF neural network. This paper creates a framework of fast identification of herba epimedii icariin in raw herba epimedii by FTIR spectra via wavelet analysis and RBF neural network.

关 键 词：淫羊藿 淫羊藿苷 傅里叶变换红外光谱 小波分析 RBF径向基神经网络 

分 类 号：O657.3[理学—分析化学]