Name
Title | ||
|---|---|---|
Cooperative sensor fusion in centralized sensor networks using Cauchy-Schwarz divergence. |
Abstract | ||
|---|---|---|
•The Cauchy–Schwarz divergence has been formulated for measuring information divergence in a centralized sensor network.•The benefit of employing Cauchy–Schwarz divergence for fusion of local updated posteriors has been demonstrated specially with imperfect consensus.•The PHD and LMB variations of the proposed solution have been derived and implemented. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.sigpro.2019.107278 | Signal Processing |
Keywords | Field | DocType |
Random finite sets,Multi-target tracking,LMB filter,Probability density function | Mathematical optimization,Fusion rules,Algorithm,Covariance intersection,Sensor fusion,Cauchy–Schwarz inequality,Poisson distribution,Wireless sensor network,Mathematics,Kullback–Leibler divergence,Bernoulli's principle | Journal |
Volume | ISSN | Citations |
167 | 0165-1684 | 1 |
PageRank | References | Authors |
0.35 | 0 | 7 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Amirali Khodadadian Gostar | 1 | 108 | 12.20 |
| Tharindu Rathnayake | 2 | 2 | 1.05 |
| Ruwan B. Tennakoon | 3 | 11 | 2.62 |
| Alireza Bab-Hadiashar | 4 | 95 | 10.01 |
| Giorgio Battistelli | 5 | 17 | 2.95 |
| Luigi Chisci | 6 | 474 | 52.30 |
| Reza Hoseinnezhad | 7 | 431 | 43.15 |