Name
Abstract | ||
|---|---|---|
•Fusion with a new (homogeneous) functional is explored.•Improved fusion can be achieved with homogeneous functionals.•Computational requirements of new functionals are equivalent to current functional.•The “min”-functional can be used in consensus with some significant advantages. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1016/j.inffus.2018.02.002 | Information Fusion |
Keywords | Field | DocType |
Data fusion,Conservative estimators,Distributed data fusion,Consensus | Convergence (routing),Disjoint sets,Pooling,Probability measure,Sensor fusion,Theoretical computer science,Probability distribution,Artificial intelligence,Mathematics,Machine learning,Bayesian probability,Bayes' theorem | Journal |
Volume | ISSN | Citations |
45 | 1566-2535 | 1 |
PageRank | References | Authors |
0.35 | 16 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Clark N. Taylor | 1 | 178 | 23.82 |
| Adrian n. Bishop | 2 | 334 | 25.08 |