Double robustness analysis for determining optimal feedforward neural network architecture

Abstract

This paper incorporates robustness into neural network modeling and proposes a novel two-phase robustness analysis approach for determining the optimal feedforward neural network (FNN) architecture in terms of Hellinger distance of probability density function (PDF) of error distribution. The proposed approach is illustrated with an example in this paper. © Springer-Verlag Berlin Heidelberg 2005.