Nonparametric Regression Modeling with Equiprobable Topographic Maps and Projection Pursuit Learning with Application to PET Image Processing

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Abstract

A recently introduced rule for equiprobable topographic map formation, called the Vectorial Boundary Adaptation Rule (VBAR), is extended and applied to nonparametric projection pursuit regression. The performance of the regression procedure is compared to that of a number of other nonparametric regression procedures. The procedure is applied to positron emission tomography (PET) images for adaptive filtering and data compression purposes.

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