Classification of incomplete feature vectors by radial basis function networks

The paper describes the use of radial basis function neural networks with Gaussian basis functions to classify incomplete feature vectors. The method uses the fact that any marginal distribution of a Gaussian distribution can be determined from the mean vector and covariance matrix of the joint distribution.

The effect of carbohydrate mouth rinsing on fencing performance and cognitive function following a fatigue inducing simulated bout of fencing in national level foil fencers

Delivered at The Physiological Society's Biomedical Basis of Elite Performance conference, Nottingham, 6-8 March 2016

An Empirical Evaluation of the Reversal Theory State Measure: Tracking Changes in the Experience of Video Commercials of Three Leading Running Brands

Abstract of paper delivered at the 17th International Reversal Theory Conference, Day 3, session 4, 01.07.15