Estimation of particle-size distribution and classifier selectivity

Robert M. West, J. C. Cullivan, Richard A Williams

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

A new, practical, and informative technique is presented for the efficient calculation of classifier efficiencies. Kernel density estimation, a well-developed statistical tool, is applied to particle-size datasets from classifier flow streams. It is demonstrated that this construction of particle-size densities is more accurate and appropriate than histograms. The resulting classifier efficiency curves then display the key features of the classifier efficiency without propagating the noise inherent in most particle-sizing techniques, and without the constraint of any selectivity curve parametrization.
Original languageEnglish
Pages (from-to)139-145
Number of pages7
JournalParticle and Particle Systems Characterization
Volume17
Issue number4
Publication statusPublished - Dec 2000

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