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<div><p>In this contribution, we use Gaussian posterior probability densities to characterize local estimates from distributed sensors, and assume that they all belong to the Riemannian manifold of Gaussian distributions. Our starting point is to introduce a proper Lie algebraic structur...

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Bibliographic Details
Main Author: Xiangbing Chen (11492719) (author)
Other Authors: Chen Chen (6544) (author), Xiaowen Lu (733561) (author)
Published: 2024
Subjects:
Infectious Diseases
Virology
Biological Sciences not elsewhere classified
Mathematical Sciences not elsewhere classified
local posterior densities
characterize local estimates
lie algebraic vector
fused covariance matrix
fixed mean vector
proposed fusion method
mean fusion
algebraic method
fused density
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theoretical convergence
starting point
riemannian manifold
gaussian submanifold
gaussian distributions
gaussian assumptions
distributed sensors
average dissimilarity
analytical form
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