Signal modeling with dynamic fuzzy sets

Signals originating from a class of time-varying systems are modeled as dynamic fuzzy sets, i.e. fuzzy sets with membership functions that change in time. A signal trajectory in feature space is mapped into a dynamic fuzzy set which quantifies and characterizes the most significant aspects of the system´s dynamics. A dynamic fuzzy set is visualized as a trajectory within a corresponding fuzzy information space. An example involving modeling of electroencephalographic signals during sleep is presented to illustrate the applicability of the method