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Application of artificial neural network to quantitative analysis of Raman spectrum

descriptionPublicationkeyboard_double_arrow_right Article 01 Sep 2006Publisher:SPIEJournal:SPIE Proceedings, volume 6,047, page 60472W (issn: 0277-786X, Copyright policy )
Authors: Chen Chen; Guoping Zhang; Gang Li;

doi: 10.1117/12.710127

Application of artificial neural network to quantitative analysis of Raman spectrum

Abstract

By means of Artificial Neural Network and Back-Propagation algorithm, the multi-component of azo-dyes can be qualitatively and quantitatively analyzed simultaneously, though their Raman spectra are overlapped. This article designed a Back-Propagation algorithm network to analyze the multi-component of azo-dyes (Sudan I and Sudan III). In conclusion, by using the Artificial Neural Network and Raman spectrum can be a good choice for resolving multi-component.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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