The paper introduces an EEG signals classifier for classification of vigilance level of a car driver. The classifier is based on the concept of radial implicative fuzzy system. The novel in the presented approach is accommodation of S-shaped fuzzy sets which can handle boundary regions of the relevant input space. Both structure and parameter learning of the system are referred to and correspon...

The aim of this paper is to introduce improvements made to a classifier based on the fuzzy similarity [1]. Improvements are based on the use of generalized Łukasiewicz-structure and weight optimization. We are presenting some new results and a more detailed description of the theoretical background and fixing some terminology compared in to our previous work [2]. The main benefits of the classi...

AN UNMANNED AERIAL VEHICLE CONTROLLER BASED ON A LEARNING FUZZY CLASSIFIER SYSTEM by YAN QU (Under the Direction of Walter D. Potter) ABSTRACT Autonomous Unmanned Aerial Vehicle (UAVs) have been increasingly employed by researchers, commercial organizations and the military to perform a variety of missions. This thesis discusses the design of an autonomous controller using a Learning Fuzzy Clas...

In an earlier work, Lee et al. [1] presented a simple and fast fuzzy classifier that employed fuzzy entropy to evaluate pattern distribution information in a pattern space. In this paper, we extend his work to propose a new fuzzy classifier based on hierarchical fuzzy entropy (FC-HFE). We retained the main parts of the original structure and modified some methods (e.g., decision of the number o...