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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Limin Fang Min Lin Yongjun Zheng |
| Copyright Year | 2008 |
| Description | Author affiliation: Coll. of Metrol. Meas. & Eng., China Jiliang Univ., Hangzhou (Limin Fang; Min Lin; Yongjun Zheng) |
| Abstract | A new method of model construction based on back-propagation artificial neural networks (BP-ANN) regression and independent component analysis (ICA) was proposed. In its application to Raman spectrum, the data of Raman spectrum were firstly compressed by wavelet transform, their independent components and the contribution matrix were then extracted by the independent component analysis, and finally, the model of the contribution matrix and concentration matrix was built by the artificial neural networks regression. The influence of the numbers of independent components and the neurons in the hidden layer on the properties of model was further analyzed. This new chemometric method has been applied to the determination of active substance content of four types of pharmaceutical tablet samples. The correlation coefficients (R) between the analytical values and the model predicted values of active substance contents are 0.995, 0.967, 0.976, and 0.982, respectively. |
| Starting Page | 429 |
| Ending Page | 433 |
| File Size | 429972 |
| Page Count | 5 |
| File Format | |
| ISBN | 9780769533049 |
| DOI | 10.1109/ICNC.2008.646 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2008-10-18 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Wavelet transforms Spectroscopy Neural networks Raman scattering Neurons Independent component analysis Artificial neural networks Wavelet analysis Data mining Pharmaceuticals |
| Content Type | Text |
| Resource Type | Article |
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