The electrocardiogram (ECG) is widely used for the diagnosis of heart diseases. However,
ECG signals are easily contaminated by different noises. This paper presents efficient …

The purpose of this review is to apply geometric frameworks in identification problems. In
contrast to the qualitative theory of dynamical systems (DSQT), the chaos and catastrophes …

Model-based engineering becomes more and more important in industrial practice. System
identification is a vital technology for producing the necessary models, and has been an …

Focusing on identification, this paper develops techniques to reconstruct zero and nonzero
elements of a sparse parameter vector θ of a stochastic dynamic system with general …

In this paper, we consider identifying Auto Regressive with eXternal input (ARX) models for
both Linear Time-Invariant (LTI) and Linear Time-Variant (LTV) systems. We aim at doing the …

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 …

A sparse estimator with close ties with the LASSO (least absolute shrinkage and selection
operator) is analysed. The basic idea of the estimator is to relax the least-squares cost …

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 …

In this paper, we study the minimization of ℓ 0 regularized optimization problems, where the
objective function is composed of a smooth convex function and the ℓ 0 regularization. We …