This article deals with the problem of detecting maritime targets embedded in
nonhomogeneous sea clutter, where the limited number of secondary data is available due …

Anomaly detection methods are devoted to target detection schemes in which no a priori
information about the spectra of the targets of interest is available. This paper reviews …

In this paper, a general class of regularized M-estimators of scatter matrix are proposed that
are suitable also for low or insufficient sample support (small n and large p) problems. The …

Financial engineering and electrical engineering are seemingly different areas that share
strong underlying connections. Both areas rely on statistical analysis and modeling of …

Given a target prior information, our goal is to propose a method for automatically separating
targets of interests from the background in hyperspectral imagery. More precisely, we regard …

A highly popular regularized (shrinkage) covariance matrix estimator is the shrinkage
sample covariance matrix (SCM) which shares the same set of eigenvectors as the SCM but …

Due to a serious shortage of training data, the performance of adaptive clutter suppression
suffers remarkable degradation in heterogeneous environments. To address this problem, a …

This paper considers the regularized Tyler's scatter estimator for elliptical distributions,
which has received considerable attention recently. Various types of shrinkage Tyler's …

Detection of buried objects such as pipes using a Ground Penetrating Radar (GPR) is
intricate for three main reasons. First, noise is important in the resulting image because of …

We study the design of portfolios under a minimum risk criterion. The performance of the
optimized portfolio relies on the accuracy of the estimated covariance matrix of the portfolio …