In this paper, we consider the following problem. Suppose a sensor is taking measurements of a dynamic process. It needs to communicate the information to an estimator over a network of communication links that can drop packets stochastically. What is the optimal processing at each node in the network that allows the estimator to estimate the state of the process? We provide a strategy that yie...

The estimation of covariance matrices multiple classes with limited training data is a difficult problem. sample matrix (SCM) known to perform poorly when the number variables large compared available samples. In order reduce mean squared error (MSE) SCM, regularized (shrinkage) SCM estimators are often used. this work, we consider (RSCM) for multiclass problems that couple together two differe...

Note. The best result in each experiment is highlighted bold.The optimal solutions of many decision problems such as the Markowitz portfolio allocation and linear discriminant analysis depend on inverse covariance matrix a Gaussian random vector. In “Distributionally Robust Inverse Covariance Estimation: Wasserstein Shrinkage Estimator,” Nguyen, Kuhn, Mohajerin Esfahani propose distributionally...

Shrinkage preliminary test estimation in exponential distribution under a precautionary loss function is considered. The minimum risk-unbiased estimator is derived and some shrinkage preliminary test estimators are proposed. We apply our results on censored data and records. The relative efficiencies of proposed estimators with respect to the minimum ‎risk-unbiased‎&...

In this paper, we consider the problem of recovering random graph signals with complex values. For general Bayesian estimation complex-valued vectors, it is known that widely-linear minimum mean-squared-error (WLMMSE) estimator can achieve a lower (MSE) than linear MSE (LMMSE) estimator. Inspired by WLMMSE estimator, in paper develop signal processing (GSP)-WLMMSE which minimizes among estimato...

This paper addresses asymptotically (in the number of measurements) minimum variance (AMV) estimators within the class of estimators based on a mixture of real and complexvalued sequence of statistics whose first covariance of its asymptotic distribution is singular. Thanks to two conditions, we extend the standard AMV estimator. We prove that these conditions are satisfied for the estimates of...