Particle Identification Using Light Scattering: A Global Optimization Problem

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Author(s): M. C. Bartholomew-Biggs (University of Hertfordshire, UK), Z. Ulanowski (University of Hertfordshire, UK)and S. Zakovic (Imperial College, UK)
Copyright: 2009
Pages: 18
Source title: Intelligent Data Analysis: Developing New Methodologies Through Pattern Discovery and Recovery
Source Author(s)/Editor(s): Hsiao-Fan Wang (National Tsing Hua University, ROC)
DOI: 10.4018/978-1-59904-982-3.ch009

Keywords: Data Mining and Databases / Information Science Reference / Knowledge Discovery / Library & Information Science

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Abstract

We discuss some experience of solving an inverse light scattering problem for single, spherical, homogeneous particles using least squares global optimization. If there is significant noise in the data, the particle corresponding to the “best” solution may not correspond well to the “actual” particle. One way of overcoming this difficulty involves the use of peak positions in the experimental data as a means of distinguishing genuine from spurious solutions. We introduce two composite approaches which combine conventional data fitting with peak-matching and show that they lead to a more robust identification procedure.

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Particle Identification Using Light Scattering: A Global Optimization Problem

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