Particle & Particle Systems Characterization, Vol.19, No.2, 65-72, 2002
Shape and size determination by laser diffraction: Parametric density estimation by neural networks
The feasibility of the inversion of laser diffraction data for size and shape distribution by neural networks has been investigated by computer simulation. The size and shape density distributions are represented by only four parameters: the peak positions and the full width at half maximum. Compared to the approach whereby the distributions are represented by a histogram with 30 grid points, the results are an order of magnitude less accurate.