Neural network with type-2 fuzzy weights adjustment for pattern recognition of the human iris biometrics

Abstract

In this paper a neural network learning method with type-2 fuzzy weight adjustment is proposed. The mathematical analysis of the proposed learning method architecture and the adaptation of type-2 fuzzy weights are presented. The proposed method is based on research of recent methods that handle weight adaptation and especially the use of fuzzy weights. In this work an ensemble neural network of three neural networks and the use of average integration to obtain the final result is presented. The proposed approach is applied to a case of time series prediction to illustrate the advantage of using type-2 fuzzy weights. © 2013 Springer-Verlag.