Bayesian Regularization and Nonnegative Deconvolution (BRAND) is proposed for estimating time delays of acoustic signals in reverberant environments. Sparsity of the nonnegative f...
Abstract— The problem of estimating the intensity process of a doubly stochastic Poisson process is analyzed. Using covariance information, a recursive linear minimum mean-square...
This paper proposes a guaranteed robust bounded-error distributed estimation algorithm. It may be employed to perform parameter estimation from data collected in a network of wire...
Given angular data 1, . . . , n [0, 2) a common objective is to estimate the density. In the case that a kernel estimator is used, bandwidth selection is crucial to the performan...
We propose a simulation-based method for calculating maximum likelihood estimators in latent variable models. The proposed method integrates a recently developed sampling strategy...