JSTOR Daily

Phase Transition of the Largest Eigenvalue for Nonnull Complex Sample Covariance Matrices

We compute the limiting distributions of the largest eigenvalue of a complex Gaussian sample covariance matrix when both the number of samples and the number of variables in each sample become large.
IEEE

Eigenvalue Estimation of Hyperspectral Wishart Covariance Matrices From Limited Number of Samples

Abstract: Estimation of covariance matrices is a fundamental step in hyperspectral remote sensing where most detection algorithms make use of the covariance matrix in whitening procedures. We present ...
JSTOR Daily

EIGENVALUE DISTRIBUTION OF A HIGH-DIMENSIONAL DISTANCE COVARIANCE MATRIX WITH APPLICATION

This is a preview. Log in through your library . Abstract We introduce a new random matrix model called the distance covariance matrix, the normalized trace of which is equivalent to the distance ...
IEEE

Minimum Eigenvalue Based Covariance Matrix Estimation with Limited Samples

Abstract: In this paper, we consider the interference rejection combining (IRC) receiver, which improves the cell-edge user throughput via suppressing inter-cell interference and requires estimating ...