A PARAMETRIC MODEL FOR FUSING HETEROGENEOUS FUZZY DATA

Presented is a model that integrates three data types (numbers, interv als, and linguistic assessments). Data of these three types come from a variety of sensors. One objective of sensor-fusion models is to prov ide a common framework for data integration, processing, and interpret ation. That is what our model does. We use a small set of artificial d ata to illustrate how problems as diverse as feature analysis, cluster ing, cluster validity, and prototype classifier design cam all be form ulated and attacked with standard methods once the data are converted to tile generalized coordinates of our model, The effects of reparamet erization on computational outputs are discussed. Numerical examples i llustrate that the proposed model affords a natural way to approach pr oblems which involve mixed data types.