Applications of Fuzzy Set Theory to Parameter Estimation and Tracking
Abstract
The paper presented here is a further development of previous work in the area of general diagnosis and estimation through use of general fuzzy set systems. An unknown state parameter vector consisting of subvectors whose values are known to lie in specified attribute domains. The vector is indexed by time and evolves according to a known process up to fuzzy errors, corresponding to prior possibility distributions which may be modeled empirically utilizing a panel of experts or obtained from physical and logical considerations. The main application of this result is that several possibility distributions describing the same object arising from different origins may be combined into a single possibility distribution by generalized conjuntion and that this distribution maximizes the utilization of information present concerning the unknown object.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jan 01, 1983
- Accession Number
- ADA241191
Entities
People
- I. R. Goodman