Automatic spectral fitting for LIBS and Raman spectra by boosted deconvolution method

IF 3.7 2区化学 Q2 AUTOMATION & CONTROL SYSTEMS

Chemometrics and Intelligent Laboratory Systems Pub Date : 2025-01-25 DOI:10.1016/j.chemolab.2025.105334

M.A. Meneses-Nava

引用次数: 0

Abstract

This study introduces a spectral analysis method known as Boosted Deconvolution Fitting (BDF) to process spectroscopic data. The BDF method enhances spectral resolution and precisely adjusts spectra by integrating boosted deconvolution for determining band profile parameters, and a multicomponent analysis technique for minor adjustments in band intensity. This technique seeks to address the shortcomings of conventional methods like the Levenberg-Marquardt algorithm (LMA), especially in terms of improving spectral resolution, accurately determining parameters of overlapping bands, and reducing sensitivity to initial conditions. The efficacy of the BDF method is affected by various factors, including the chosen band profile type (Gaussian or Lorentzian), the signal-to-noise ratio (SNR) of the dataset, and the separation and relative intensities of the spectral bands.

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来源期刊

Chemometrics and Intelligent Laboratory Systems 工程技术-分析化学

CiteScore

7.50

自引率

7.70%

发文量

169

审稿时长

3.4 months

期刊介绍： Chemometrics and Intelligent Laboratory Systems publishes original research papers, short communications, reviews, tutorials and Original Software Publications reporting on development of novel statistical, mathematical, or computer techniques in Chemistry and related disciplines. Chemometrics is the chemical discipline that uses mathematical and statistical methods to design or select optimal procedures and experiments, and to provide maximum chemical information by analysing chemical data. The journal deals with the following topics: 1) Development of new statistical, mathematical and chemometrical methods for Chemistry and related fields (Environmental Chemistry, Biochemistry, Toxicology, System Biology, -Omics, etc.) 2) Novel applications of chemometrics to all branches of Chemistry and related fields (typical domains of interest are: process data analysis, experimental design, data mining, signal processing, supervised modelling, decision making, robust statistics, mixture analysis, multivariate calibration etc.) Routine applications of established chemometrical techniques will not be considered. 3) Development of new software that provides novel tools or truly advances the use of chemometrical methods. 4) Well characterized data sets to test performance for the new methods and software. The journal complies with International Committee of Medical Journal Editors'' Uniform requirements for manuscripts.