Rapid Quantitative Analysis of IR Absorption Spectra for Trace Gas Detection by Artificial Neural Networks Trained with Synthetic Data

Infrared absorption spectroscopy is a widely used tool to quantify and monitor compositions of gases. The concentration information is often retrieved by fitting absorption profiles to the acquired spectra, utilizing spectroscopic databases. In complex gas matrices an expanded parameter space leads...

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Autori principali:	Jens Goldschmidt, Leonard Nitzsche, Sebastian Wolf, Armin Lambrecht, Jürgen Wöllenstein
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	MDPI AG 2022-01-01
Serie:	Sensors
Soggetti:	spectral analysis quantitative gas analysis machine learning artificial neural networks dual comb spectroscopy broadband spectroscopy
Accesso online:	https://www.mdpi.com/1424-8220/22/3/857
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