Identification for robust control must deliver not only a nominal model, but also a reliable
estimate of the uncertainty associated with the model. This paper addresses recent …

In this paper, we present a unified framework for solving a general class of problems arising
in the context of set-membership estimation/identification theory. More precisely, the paper …

A new powerful and flexible fuzzy algorithm for nonlinear dynamic system identification is
presented. It is based on the identification of the derivative of the system state, instead of the …

In this paper, we study the size of the membership-set for system identification in a
probabilistic framework. Assuming that the regressors are persistently exciting and the …

Most of the previous signal processing identification results have been achieved using either
time-domain or frequency-domain algorithms. In this study, the two methods were combined …

Non-asymptotic bounds for the linfty estimator in linear regression with uniform noise Page 1
Bernoulli 30(1), 2024, 534–553 https://doi.org/10.3150/23-BEJ1607 Non-asymptotic bounds for …

We consider the CEO problem for non-regular source distributions (such as uniform or
truncated Gaussian). A group of agents observe independently corrupted versions of data …

The CEO problem has received much attention since first introduced by Berger et al., but
there are limited results on non-Gaussian models with non-quadratic distortion measures. In …

In this paper, we propose a mixed approach to identification of linear dynamic systems
corrupted by additive, amplitude bounded white noise. To come up with an estimate of the …

A new family of MLE type Lp estimators for model order reduction in dynamical systems
identification is presented in this paper. A family of Lp distributions proposed in this work …