Abstract

A stochastic inverse technique based on a genetic algorithm (GA) to invert particle-size distribution from angular light-scattering data is developed. This inverse technique is independent of any given a priori information of particle-size distribution. Numerical tests show that this technique can be successfully applied to inverse problems with high stability in the presence of random noise and low susceptibility to the shape of distributions. It has also been shown that the GA-based inverse technique is more efficient in use of computing time than the inverse Monte Carlo method recently developed by Ligon et al. [Appl. Opt. 35, 4297 (1996)].

© 1999 Optical Society of America

Numerical study of particle-size distributions retrieved from angular light-scattering data using an evolution strategy with the Fraunhofer approximation

Javier Vargas-Ubera, Juan Jaime Sánchez-Escobar, J. Félix Aguilar, and David Michel Gale
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Determination of aerosol parameters from light-scattering data using an inverse Monte Carlo technique

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Nonnegative least-squares truncated singular value decomposition to particle size distribution inversion from dynamic light scattering data

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Reconstruction of particle-size distributions from light-scattering patterns using three inversion methods

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