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- W2972732884 abstract "High-resolution absorption spectroscopy is a promising method for non-invasive process monitoring, but the computational effort required to evaluate the data can be prohibitive in high-speed, real-time applications. This study presents a fast method to estimate absorbance spectra from transmitted intensity signals. We employ Bayesian statistics to combine a measurement model with prior information about the shape of the baseline intensity and absorbance spectrum. The resulting linear least-squares problem shifts most of the computational effort to a preparation step, thereby facilitating quick processing and low latency for any number of measurements. The method is demonstrated on simulated tunable diode laser absorption spectroscopy data with additive noise and a fluctuating fringe. Results were highly accurate and the method was computationally efficient, having a processing time of only 2 ms per spectrum." @default.
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- W2972732884 date "2019-09-11" @default.
- W2972732884 modified "2023-10-09" @default.
- W2972732884 title "Efficient Bayesian inference of absorbance spectra from transmitted intensity spectra" @default.
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- W2972732884 doi "https://doi.org/10.1364/oe.27.026893" @default.
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