2 citations · 2 across the 5 of their papers we have counts for
6 papers
Prediction Error Method for Identification of Subnetworks of Dynamical Systems
João Victor Galvão da Mata, Anders Hansson, Martin S. Andersen
This paper considers prediction-error identification of a subnetwork embedded in a dynamic network. Measured boundary signals entering the subnetwork are appended to the exogenous…
Informativity and Identifiability for Identification of Networks of Dynamical Systems
Anders Hansson, João Victor Galvão da Mata, Martin S. Andersen
In this paper, we show how informativity and identifiability for networks of dynamical systems can be investigated using Gröbner bases. We provide a sufficient condition for generi…
Maximum Likelihood Estimation of Dynamic Sub-Networks with Missing Data
João Victor Galvão da Mata, Anders Hansson, Martin S. Andersen
Maximum likelihood estimation is effective for identifying dynamical systems, but applying it to large networks becomes computationally prohibitive. This paper introduces a maximum…
Maximum Likelihood Estimation for System Identification of Networks of Dynamical Systems
Anders Hansson, João Victor Galvão da Mata, Martin S. Andersen
This paper investigates maximum likelihood estimation for direct system identification in networks of dynamical systems. We establish that the proposed approach is both consistent…
AdaSub: Stochastic Optimization Using Second-Order Information in Low-Dimensional Subspaces
João Victor Galvão da Mata, Martin S. Andersen
We introduce AdaSub, a stochastic optimization algorithm that computes a search direction based on second-order information in a low-dimensional subspace that is defined adaptively…
Direct System Identification of Dynamical Networks with Partial Measurements: a Maximum Likelihood Approach
João Victor Galvão da Mata, Anders Hansson, Martin S. Andersen
This paper introduces a novel direct approach to system identification of dynamic networks with missing data based on maximum likelihood estimation. Dynamic networks generally pres…