Radial Basis Function Artificial Neural Networks and Fuzzy Logic

Abstract

this paper we examine the Radial Basis Function (RBF) artificial neural network and its application in the approximate reasoning process. The paper opens with a brief description of this type of network and its origins, and then goes on to show one way in which it can be used to perform approximate reasoning. We then consider the relation between a modified form of RBF network and a fuzzy controller, and conclude that they can be identical. Applications to mobile robot navigation will be described. The final part of the paper will consider a novel type of network, the Artificial Neural Inference (ANI) network, which whilst related to the RBF network, can perform max/min compositional inference. Making use of some new results in analysis, it is also possible to propose an adaptive form of this network, and it is on this network that our current work is focused