SCPD: Splitting-based constrained parallel factor decomposition for fluorescence spectroscopy analysis

IF 3.7 2区化学 Q2 AUTOMATION & CONTROL SYSTEMS

Chemometrics and Intelligent Laboratory Systems Pub Date : 2025-07-25 DOI:10.1016/j.chemolab.2025.105487

Ke Wang , Ban-teng Liu

引用次数: 0

Abstract

The fluorescence spectroscopy offers a reliable and fast detection method for quantitative and qualitative information in modern industrial processes. In fluorescence spectroscopy analysis, a common problem is how to extract and represent the latent structure from original data in tensor form. However, existing studies have difficulties in efficiently obtaining precise mathematical results for constrained least-squares problems. In this paper, a new split-based constrained decomposition algorithm is proposed, building upon the parallel factor analysis and alternating direction method of multipliers. Combined with parameter selection strategies, it is shown that this distributed algorithm is suitable for parallel implementation with a good convergence property. Experiments on data taken from synthetic and real-world data indicate its potential utility in fluorescence spectroscopy analysis and other application domains.

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基于分裂的约束平行因子分解在荧光光谱分析中的应用

荧光光谱技术为现代工业过程中的定量和定性信息提供了一种可靠、快速的检测方法。在荧光光谱分析中，如何从原始数据中提取并以张量形式表示潜在结构是一个常见的问题。然而，现有的研究难以有效地获得约束最小二乘问题的精确数学结果。本文在并行因子分析和乘法器交替方向法的基础上，提出了一种新的基于分割的约束分解算法。结合参数选择策略，表明该分布式算法具有良好的收敛性，适合并行实现。对合成数据和实际数据的实验表明，它在荧光光谱分析和其他应用领域具有潜在的实用性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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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.