Francesco Amato

TL;DR: This paper couple an integrate-and-fire model with information theory variables to analyse the extent of information in a network of nerve cells and provides an estimate of the information in the network in bits as a function of cell density and short-term depression time.

TL;DR: In this chapter, after an overview of the state-of-the-art research on BCI systems, the spatial filtering problem in EEG signals acquisition will be illustrated and a spatial filtering algorithm, known as ICA (Independent Component Analysis) and its application will be discussed.

TL;DR: In this paper, the problem of the estimation of the domain of attraction for Impulsive Dynamical Systems (IDSs) is tackled in terms of Linear Matrix Inequalities problems, and sufficient conditions to determine whether a polytope belongs to the zero equilibrium point domain for both time-dependent and state-dependent IDS, when a nonlinear quadratic continuous-time dynamic is considered.

TL;DR: This work shows how a control-theoretic analysis of the robustness of a model of the GAL regulatory network may be used to establish the model’s plausibility in characterizing the persistent memory of different carbon sources, without the need for extensive simulations.

TL;DR: A novel and accurate model of the hysteresis of the mechanical response of PAMs is presented, which provides some advantages in terms of ease of parameter identification and implementation into a control system, thanks to the use of a limited number of parameters.