9 citations · 11 across the 13 of their papers we have counts for
20 papers
The internal model principle in reservoir computing
Danyal Saqib, Alberto Padoan
The paper studies learning in reservoir computing systems through the lens of the internal model principle. The key idea is to model training signals as outputs of an exogenous sig…
Open Quadratic Optimization Programs
Alberto Padoan
The paper studies open optimization programs, that is, parametric optimization programs viewed as open systems, and their interconnection. Each open optimization program is assigne…
On Dominant Manifolds in Reservoir Computing Networks
Noa Kaplan, Alberto Padoan, Anastasia Bizyaeva
Understanding how training shapes the geometry of recurrent network dynamics is a central problem in time-series modeling. We study the emergence of low-dimensional dominant manifo…
Scaled Relative Graphs in Normed Spaces
Alberto Padoan
The paper extends the Scaled Relative Graph (SRG) framework of Ryu, Hannah, and Yin from Hilbert spaces to normed spaces. Our extension replaces the inner product with a regular pa…
From time series to dissipativity of linear systems with dynamic supply rates
Henk J. van Waarde, Jeremy Coulson, Alberto Padoan
This paper studies the problem of verifying dissipativity of linear time-invariant (LTI) systems using input-output data. We leverage behavioral systems theory to express dissipati…
Geometrically robust least squares through manifold optimization
Jeremy Coulson, Alberto Padoan, Cyrus Mostajeran
This paper presents a methodology for solving a geometrically robust least squares problem, which arises in various applications where the model is subject to geometric constraints…
Robust Least-Squares Optimization for Data-Driven Predictive Control: A Geometric Approach
Shreyas Bharadwaj, Bamdev Mishra, Cyrus Mostajeran +3
The paper studies a geometrically robust least-squares problem that extends classical and norm-based robust formulations. Rather than minimizing residual error for fixed or perturb…
Least Squares Model Reduction: A Two-Stage System-Theoretic Interpretation
Alberto Padoan
Model reduction simplifies complex dynamical systems while preserving essential properties. This paper revisits a recently proposed system-theoretic framework for least squares mom…
Distances between finite-horizon linear behaviors
Alberto Padoan, Jeremy Coulson
The paper introduces a class of distances for linear behaviors over finite time horizons. These distances allow for comparisons between finite-horizon linear behaviors represented…
Urban traffic congestion control: a DeePC change
Alessio Rimoldi, Carlo Cenedese, Alberto Padoan +2
Urban traffic congestion remains a pressing challenge in our rapidly expanding cities, despite the abundance of available data and the efforts of policymakers. By leveraging behavi…
Data-driven representations of conical, convex, and affine behaviors
Alberto Padoan, Florian Dörfler, John Lygeros
The paper studies conical, convex, and affine models in the framework of behavioral systems theory. We investigate basic properties of such behaviors and address the problem of con…
Controller implementability: a data-driven approach
Alberto Padoan, Jeremy Coulson, Florian Dörfler
We study the controller implementability problem, which seeks to determine if a controller can make the closed-loop behavior of a given plant match that of a desired reference beha…
A quantitative and constructive proof of Willems' Fundamental Lemma and its implications
Julian Berberich, Andrea Iannelli, Alberto Padoan +3
Willems' Fundamental Lemma provides a powerful data-driven parametrization of all trajectories of a controllable linear time-invariant system based on one trajectory with persisten…
Behavioral uncertainty quantification for data-driven control
Alberto Padoan, Jeremy Coulson, Henk J. van Waarde +2
This paper explores the problem of uncertainty quantification in the behavioral setting for data-driven control. Building on classical ideas from robust control, the problem is reg…
Circuit Model Reduction with Scaled Relative Graphs
Thomas Chaffey, Alberto Padoan
Continued fractions are classical representations of complex objects (for example, real numbers) as sums and inverses of simpler objects (for example, integers). The analogy in lin…
Model reduction by least squares moment matching for linear and nonlinear systems
Alberto Padoan
The paper addresses the model reduction problem for linear and nonlinear systems using the notion of least squares moment matching. For linear systems, the main idea is to approxim…
On model reduction by least squares moment matching
Alberto Padoan
The paper addresses the model reduction problem by least squares moment matching for continuous-time, linear, time-invariant systems. The basic idea behind least squares moment mat…
Model reduction by balanced truncation of dominant Lure systems
Alberto Padoan, Fulvio Forni, Rodolphe Sepulchre
The paper presents a model reduction framework geared towards the analysis and design of systems that switch and oscillate. While such phenomena are ubiquitous in nature and engine…
The norm as the differential gain of a -dominant system
Alberto Padoan, Fulvio Forni, Rodolphe Sepulchre
The differential gain of a linear, time-invariant, -dominant system is shown to coincide with the norm of its transfer function ,…
Dominance margins for feedback systems
Alberto Padoan, Fulvio Forni, Rodolphe Sepulchre
The paper introduces notions of robustness margins geared towards the analysis and design of systems that switch and oscillate. While such phenomena are ubiquitous in nature and in…