Title :
Comparison of techniques for combination of evidence in a signal detection task
Author_Institution :
Dept. of Electr. Eng., Pittsburgh Univ., PA, USA
fDate :
30 Sep-2 Oct 1991
Abstract :
Signal decision models based on Dempster-Shafer and fuzzy set theories were developed to facilitate the implementation of a rule-based interpretation system for sensory evoked potential waveforms. The models do not require a priori probabilities, and they provide measures of uncertainty. The two models were applied to a set of brainstem auditory evoked potential waveforms. Both had lower absolute error rates than discriminant analysis, although they yielded large numbers of uncertain waveforms. The fuzzy set approach may be less sensitive to the exact form of the membership functions
Keywords :
computerised signal processing; fuzzy logic; fuzzy set theory; knowledge based systems; signal detection; Dempster-Shafer; brainstem auditory evoked; discriminant analysis; fuzzy set theories; knowledge-based system; rule-based interpretation system; sensory evoked potential waveforms; signal decision models; signal detection task; uncertainty; Brain modeling; Error analysis; Fuzzy reasoning; Fuzzy set theory; Fuzzy sets; Fuzzy systems; Hybrid intelligent systems; Measurement uncertainty; Prototypes; Signal detection;
Conference_Titel :
Developing and Managing Expert System Programs, 1991., Proceedings of the IEEE/ACM International Conference on
Conference_Location :
Washington, DC
Print_ISBN :
0-8186-2250-4
DOI :
10.1109/DMESP.1991.171706