4 citations · 6 across the 4 of their papers we have counts for
5 papers
Stability properties of Minimal Gated Unit neural networks
Stefano De Carli, Davide Previtali, Mirko Mazzoleni +1
In this work, we address the need for efficient and formally stable Recurrent Neural Networks (RNNs) in environments with limited computational resources by analyzing the stability…
Integrating Biological-Informed Recurrent Neural Networks for Glucose-Insulin Dynamics Modeling
Stefano De Carli, Nicola Licini, Davide Previtali +2
Type 1 Diabetes (T1D) management is a complex task due to many variability factors. Artificial Pancreas (AP) systems have alleviated patient burden by automating insulin delivery t…
Infinity-norm-based Input-to-State-Stable Long Short-Term Memory networks: a thermal systems perspective
Stefano De Carli, Davide Previtali, Leandro Pitturelli +3
Recurrent Neural Networks (RNNs) have shown remarkable performances in system identification, particularly in nonlinear dynamical systems such as thermal processes. However, stabil…
Chaos-Free Networks are Stable Recurrent Neural Networks
Stefano De Carli, Davide Previtali, Mirko Mazzoleni +1
Gated Recurrent Neural Networks (RNNs) are widely used for nonlinear system identification due to their high accuracy, although they often exhibit complex, chaotic dynamics that ar…
A virtual sensor fusion approach for state of charge estimation of lithium-ion cells
Davide Previtali, Daniele Masti, Mirko Mazzoleni +1
This paper addresses the estimation of the State Of Charge (SOC) of lithium-ion cells via the combination of two widely used paradigms: Kalman Filters (KFs) equipped with Equivalen…