Signal modeling with dynamic fuzzy sets

Author

Kosanovic, Bogdun R. ; Chaparro, Luis E. ; Sclabassi, Robert J.

Author_Institution

Lab. for Comput. Neurosci., Pittsburgh Univ., PA, USA

Volume

5

fYear

1996

fDate

7-10 May 1996

Firstpage

2829

Abstract

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

Keywords

electroencephalography; fuzzy set theory; medical diagnostic computing; medical signal processing; signal representation; time-varying systems; EEG; dynamic fuzzy sets; electroencephalographic signals; feature space; fuzzy information space; membership functions; signal modeling; signal representation; signal trajectory; sleep; system dynamics; time-varying systems; Differential equations; Extraterrestrial measurements; Fuzzy set theory; Fuzzy sets; Motion analysis; Signal processing; Surgery; Time varying systems; Trajectory; Visualization;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 1996. ICASSP-96. Conference Proceedings., 1996 IEEE International Conference on

Conference_Location

Atlanta, GA

ISSN

1520-6149

Print_ISBN

0-7803-3192-3

Type

conf

DOI

10.1109/ICASSP.1996.550142

Filename

550142