Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10360041 | Information Fusion | 2005 | 10 Pages |
Abstract
This second part develops an entirely new decision fusion rule from the decision rule of Part I. The decision fusion rule is restructured to produce a recursive algorithm that has similarities with the Kalman filter. The performance characteristics of the recursive algorithm and a handful of extensions are compared to a recursive Bayesian decision fusion algorithm through the analysis of a simple decision problem.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Vision and Pattern Recognition
Authors
Michael B. Hurley,