A New Method for Representing Linguistic Quantifications by Random Sets with Applications to Tracking and Data Fusion
Abstract
There is an obvious need to be able to integrate both linguistic-based and stochastic-based input information in data fusion. In particular, this need is critical in addressing problems of track association, including cyber-state intrusions. This paper treats this issue through a new insight into how three apparently distinct mathematical tools can be combined: "boolean relational event algebra" (BREA), "one point random set coverage representations of fuzzy sets" (OPRSC), and "complexity-reducing algorithm for near optimal fusion" (CRANOF).
Document Details
- Document Type
- Technical Report
- Publication Date
- Jul 08, 2002
- Accession Number
- ADA506905
Entities
People
- Donald Bamber
- Hung T. Nguyen
- I. R. Goodman
- William C. Torrez
Organizations
- Naval Information Warfare Systems Command