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most citedAn incremental input-to-state stability condition for a generic class of recurrent neural networks

2 citations · 3 across the 4 of their papers we have counts for

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eess.SY2022★ 2 cited

An incremental input-to-state stability condition for a generic class of recurrent neural networks

William D'Amico, Alessio La Bella, Marcello Farina

This paper proposes a novel sufficient condition for the incremental input-to-state stability of a generic class of recurrent neural networks (RNNs). The established condition is c…

eess.SY2022

Virtual Reference Feedback Tuning for linear discrete-time systems with robust stability guarantees based on Set Membership

William D'Amico, Marcello Farina

In this paper we propose a novel methodology that allows to design, in a purely data-based fashion and for linear single-input and single-output systems, both robustly stable and p…