Abstract
A classification architecture is presented in which the domain knowledge and belief measures are represented using the principles of possibility theory. The representations and support generation strategies are designed for a classification system whose objective is to identify radar types from signals received by passive sensors. A measure of belief is generated to indicate the support for each of the alternatives on the basis of the acquired evidence, using a possibility distribution over the frame of discernment. The immediate transformation of evidence to possibility distributions avoids the computational difficulties associated with utilizing the joint possibility distribution over the entire set of attributes that characterize the domain objects. The desired possibility distribution is obtained by combining the compatibility measures for each hypothesis independently.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the IEEE National Aerospace and Electronics Conference |
| Publisher | IEEE |
| Pages | 1048-1052 |
| Number of pages | 5 |
| DOIs | |
| State | Published - 1989 |
| Event | IEEE 1989 National Aerospace and Electronics Conference - Dayton, United States Duration: May 22 1989 → May 26 1989 |
Conference
| Conference | IEEE 1989 National Aerospace and Electronics Conference |
|---|---|
| Abbreviated title | NAECON 1989 |
| Country/Territory | United States |
| City | Dayton |
| Period | 5/22/89 → 5/26/89 |
ASJC Scopus Subject Areas
- General Engineering
Keywords
- Computer architecture
- Computer science
- Current measurement
- Fuzzy reasoning
- Fuzzy set theory
- Passive radar
- Possibility theory
- Sensor phenomena and characterization
- Signal design
- Signal generators
Disciplines
- Computer Sciences
- Engineering
- Mathematics