| 人工神经网络法鉴别红外光谱 |
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| 引用本文： | 李燕,王俊德,王连军.人工神经网络法鉴别红外光谱[J].光谱学与光谱分析,2000,20(4):477-479. |
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| 作者姓名： | 李燕 王俊德 王连军 |
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| 作者单位： | 南京理工大学现代光谱研究室,210014,南京 |
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| 基金项目： | 国家自然科学基金，国家教委博士点基金，江苏省科学技术委员会资助 |
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| 摘 要： | 本文将反向传播人工神经网络（ＢＰ－ＡＮＮ）用于ＦＴＩＲ，鉴别未知化合物。结果表明，当训练集样本不含噪声时，纯光谱的预测结果很好。而当训练集样本有少量噪声干扰时，预测结果随预测集样本的不同，而得到不同的改善。
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| 关 键 词： | 红外光谱 人工神经网络 相似系数 鉴别 |
Artificial Neural Network for the Identification of Infrared Spectra |
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| Yan LI,Junde WANG,Lianjun WANG.Artificial Neural Network for the Identification of Infrared Spectra[J].Spectroscopy and Spectral Analysis,2000,20(4):477-479. |
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| Authors: | Yan LI Junde WANG Lianjun WANG |
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| Institution: | Laboratory of Advanced Spectroscopy, Nanjing University of Science and Technology, 210014 Nanjing. |
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| Abstract: | An Artificial Neural Network(ANN) was used to identify unknown infrared spectra.The Neural Network consisted of three layers was trained by a back propagation algorithm.In the first step of the experiment,the training set was pure spectra information,the neural network can only identify correctly the spectra without noise or with relatively low noise,in the second step,the training set was spectra information with relatively low noise,the identification results of the test sets was better than that of the first step.The results showed that artificial neural network can be used as a powerful tool in solving classification and identification problems. |
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| Keywords: | FTIR Artificial neural network Similarity index |
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