A Blind Source Separation Method Applied to Simultaneous Kinetic Multicomponent Determination

Abstract:

A multi-dimensional data processing method, independent component analysis-based principal component regression (ICA-PCR) was developed for simultaneous kinetic determination of Cu (II), Fe (III) and Ni (II). Independent component analysis is a newly developed signal processing technique aiming at solving related blind source separation (BSS) problem. One program, PICAPCR, was designed to perform relative calculations. Experimental results showed the ICA-PCR method to be successful for simultaneous multicomponent kinetic determination even where there was severe overlap of spectra.

• Periodical: Applied Mechanics and Materials (Volumes 380-384)
• Pages: 3678-3681
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.380-384.3678
• Online since: August 2013
• Authors: Gao Ling, Shou Xin Ren
• Keywords: Blind Source Separation, Independent Component Analysis (ICA), Multi-Dimensional Data Processing, Principal Component Regression

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