Aluminum electrolysis cells are characterized by harsh environments where several
measurements have to be done manually. Due to the operational costs related to manual …

We study discrete time dynamical systems governed by the state equation $ h_ {t+ 1}=\phi
(Ah_t+ Bu_t) $. Here $ A, B $ are weight matrices, $\phi $ is an activation function, and $ u_t …

Abstract Structure identification of large-scale but sparse-flow interconnected dynamical
systems from limited data has recently gained much attention in the control and signal …

Selection of an efficient model parametrization (model order, delay, etc.) has crucial
importance in parametric system identification. It navigates a trade-off between …

The development of online algorithms to track time-varying systems has drawn a lot of
attention in the last years, in particular in the framework of online convex optimization …

Autoregressive exogenous (ARX) systems are the general class of input-output dynamical
system used for modeling stochastic linear dynamical system (LDS) including partially …

Current sensor is an important part of Battery Management System (BMS). Current
information of a battery is very important to estimate the value of State of Charge (SOC) as a …

This study focuses on the parameter estimation of Hammerstein non‐linear systems with
unknown time‐delay and coloured noise. By means of the compressed sensing recovery …

This paper focuses on the identification of multiple-input single-output output-error systems
with unknown time-delays. Since the time-delays are unknown, an identification model with …

In this tutorial, we review some of the recent results concerning Compressive System
Identification (CSI)(identification from few measurements) of sparse channels (and in …