Search Results - "Chiuso, Alessandro"
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1
The role of vector autoregressive modeling in predictor-based subspace identification
Published in Automatica (Oxford) (01-06-2007)“…Subspace identification for closed loop systems has been recently studied by several authors. A class of new and consistent closed-loop subspace algorithms is…”
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2
A Bayesian approach to sparse dynamic network identification
Published in Automatica (Oxford) (01-08-2012)“…Modeling and identification of high dimensional systems, involving signals with many components, poses severe challenges to off-the-shelf techniques for system…”
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3
Tuning complexity in regularized kernel-based regression and linear system identification: The robustness of the marginal likelihood estimator
Published in Automatica (Oxford) (01-08-2015)“…Kernel-based regularization approaches have been successfully applied in the last years for regression purposes. Recently, these machine learning techniques…”
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4
Sparse DCM for whole-brain effective connectivity from resting-state fMRI data
Published in NeuroImage (Orlando, Fla.) (01-03-2020)“…Contemporary neuroscience has embraced network science and dynamical systems to study the complex and self-organized structure of the human brain. Despite the…”
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Machine Learning Estimation of the Phase at the Fading Points of an OFDR-Based Distributed Sensor
Published in Sensors (Basel, Switzerland) (01-01-2023)“…The paper reports a machine learning approach for estimating the phase in a distributed acoustic sensor implemented using optical frequency domain…”
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Distributed Kalman filtering based on consensus strategies
Published in IEEE journal on selected areas in communications (01-05-2008)“…In this paper, we consider the problem of estimating the state of a dynamical system from distributed noisy measurements. Each agent constructs a local…”
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7
Macroscale coupling between structural and effective connectivity in the mouse brain
Published in Scientific reports (07-02-2024)“…Exploring how the emergent functional connectivity (FC) relates to the underlying anatomy (structural connectivity, SC) is one of the major goals of modern…”
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8
Controlling target brain regions by optimal selection of input nodes
Published in PLoS computational biology (01-01-2024)“…The network control theory framework holds great potential to inform neurostimulation experiments aimed at inducing desired activity states in the brain…”
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9
Maximum Entropy vector kernels for MIMO system identification
Published in Automatica (Oxford) (01-05-2017)“…Recent contributions have framed linear system identification as a nonparametric regularized inverse problem. Relying on ℓ2-type regularization which accounts…”
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A New Kernel-Based Approach for NonlinearSystem Identification
Published in IEEE transactions on automatic control (01-12-2011)“…We present a novel nonparametric approach for identification of nonlinear systems. Exploiting the framework of Gaussian regression, the unknown nonlinear…”
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11
Optimal Synchronization for Networks of Noisy Double Integrators
Published in IEEE transactions on automatic control (01-05-2011)“…In this technical note, we present a novel synchronization protocol to synchronize a network of controlled discrete-time double integrators which are…”
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12
Consistency analysis of some closed-loop subspace identification methods
Published in Automatica (Oxford) (01-03-2005)“…We study statistical consistency of two recently proposed subspace identification algorithms for closed-loop systems. These algorithms may be seen as…”
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13
Sparse plus low rank network identification: A nonparametric approach
Published in Automatica (Oxford) (01-02-2017)“…Modeling and identification of high-dimensional stochastic processes is ubiquitous in many fields. In particular, there is a growing interest in modeling…”
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14
The harmonic analysis of kernel functions
Published in Automatica (Oxford) (01-08-2018)“…Kernel-based methods have been recently introduced for linear system identification as an alternative to parametric prediction error methods. Adopting the…”
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15
Control-oriented regularization for linear system identification
Published in Automatica (Oxford) (01-05-2021)“…In this paper, we develop a novel theoretical framework for control-oriented identification, based on a Bayesian perspective on modeling. Specifically, we show…”
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16
Data-driven predictive control in a stochastic setting: a unified framework
Published in Automatica (Oxford) (01-06-2023)“…Data-driven predictive control (DDPC) has been recently proposed as an effective alternative to traditional model-predictive control (MPC) for its unique…”
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17
Linear system identification using the sequential stabilizing spline algorithm
Published in Automatica (Oxford) (01-04-2022)“…Paradoxically, even if stability (with its many facets) is the key concept in control, including system stability constraints in an identification procedure is…”
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18
Information fusion strategies and performance bounds in packet-drop networks
Published in Automatica (Oxford) (01-07-2011)“…In this paper, we discuss suboptimal distributed estimation schemes for stable stochastic discrete time linear systems under the assumptions that…”
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Prediction error identification of linear systems: A nonparametric Gaussian regression approach
Published in Automatica (Oxford) (01-02-2011)“…A novel Bayesian paradigm for the identification of output error models has recently been proposed in which, in place of postulating finite-dimensional models…”
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System Identification Via Sparse Multiple Kernel-Based Regularization Using Sequential Convex Optimization Techniques
Published in IEEE transactions on automatic control (01-11-2014)“…Model estimation and structure detection with short data records are two issues that receive increasing interests in System Identification. In this paper, a…”
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