Li Y, Wang J, Wang L
Laboratory of Advanced Spectroscopy, Nanjing University of Science and Technology, 210014 Nanjing.
Guang Pu Xue Yu Guang Pu Fen Xi. 2000 Aug;20(4):477-9.
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.
使用人工神经网络(ANN)来识别未知红外光谱。由三层组成的神经网络通过反向传播算法进行训练。在实验的第一步,训练集是纯光谱信息,神经网络只能正确识别无噪声或噪声相对较低的光谱;在第二步,训练集是噪声相对较低的光谱信息,测试集的识别结果比第一步更好。结果表明,人工神经网络可作为解决分类和识别问题的有力工具。