In this paper we consider the problem of estimating the eigenvectors of the sample covariance matrix of decentralized measurements in a distributed fashion.
The protocol we propose is a fully decentralized method for estimating the eigenvectors of the sample covariance matrix of sensor network data. The scheme ...
Oct 22, 2024 · This paper introduces a multiple-access coding technique that is tailored to solve average consensus problems efficiently in wireless networks.
Estimation of covariance matrices then deals with the question of how to approximate the actual covariance matrix on the basis of a sample from the multivariate ...
Missing: decentralized | Show results with:decentralized
People also ask
What is covariance estimation?
What is the covariance of the sample?
What is the covariance between two estimates?
What is the empirical covariance estimate?
Dec 7, 2015 · Abstract: In this paper, we consider performance analysis of the decentralized power method for the eigendecomposition of the sam-.
We describe a distributed adaptive algorithm to estimate the eigenvectors corresponding to the Q largest or smallest eigenvalues of the network-wide sensor ...
To obtain the actual state estimate and its associated covariance, one must solve Eqs. 7 and 8 together to back out the state estimate and covariance matrix. 3.
This study focuses on the estimation of the sample covariance matrix from low-dimensional random projections of data known as compressive measurements.
We first revisit the problem of fusing several state estimates in a central fusion node and introduce the square-root decomposition method to reconstruct the ...
Sep 20, 2015 · They developed a new estimator which is the weighted average between the sample covariance and the identity matrix. They mentioned in the ...