Abstract: In this paper, we propose two new algorithms for maximum-likelihood estimation (MLE) of high dimensional sparse covariance matrices. Unlike most of the state-of-the-art methods, which either ...
Abstract: Over the past few decades, numerous adaptive Kalman filters (AKFs) have been proposed. However, achieving online estimation with both high estimation accuracy and fast convergence speed is ...