Bayesian Interpretation of Adaptive Fuzzy Neural Network Model

Abstract

This paper conveys Bayesian interpretation of improved integrated adaptive fuzzy clustering(IAFC), which is one of the adaptive fuzzy neural network models and suggests upper bound of vigilance parameter, which gives us a guideline to endow IAFC with flexibility within the framework of minimum risk classifier. Besides, we proposed the off-line and on-line learning strategy of IAFC. The proposed techniques are applied to construct facial expression recognition system dealing with neutral, happy, sad, and angry. We empirically show that proposed methods are able to outperform the conventional IAFC.