289 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University of LuxembourgLU34 papers
- University of CambridgeGB5 papers
- Centre Hospitalier de LuxembourgLU3 papers
- Institute for Systems BiologyUS3 papers
- Aalto UniversityFI2 papers
- Adobe Systems (United States)US2 papers
- KTH Royal Institute of TechnologySE2 papers
- Trier University of Applied SciencesDE2 papers
- University of Newcastle AustraliaAU2 papers
- AlbaNovaSE1 paper
- Cluster of Excellence on Plant SciencesDE1 paper
- Cornell UniversityUS1 paper
6 papers · 1 filter
Functional observability and target state estimation in large-scale networks
Arthur N. Montanari, Chao Duan, Luis A. Aguirre +1
The quantitative understanding and precise control of complex dynamical systems can only be achieved by observing their internal states via measurement and/or estimation. In large-…
Data-driven Discovery of Cyber-Physical Systems
Ye Yuan, Xiuchuan Tang, Wei Pan +5
Cyber-physical systems (CPSs) embed software into the physical world. They appear in a wide range of applications such as smart grids, robotics, intelligent manufacture and medical…
An Approach to Sparse Continuous-time System Identification from Unevenly Sampled Data
Rui Teixeira Ribeiro, Alexandre Mauroy, Jorge Goncalves
In this work, we address the problem of identifying sparse continuous-time dynamical systems when the spacing between successive samples (the sampling period) is not constant over…
Inverse Problems for Matrix Exponential in System Identification: System Aliasing
Zuogon Yue, Johan Thunberg, Jorge Goncalves
This note addresses identification of the -matrix in continuous time linear dynamical systems on state-space form. If this matrix is partially known or known to have a sparse st…
Linear identification of nonlinear systems: A lifting technique based on the Koopman operator
Alexandre Mauroy, Jorge Goncalves
We exploit the key idea that nonlinear system identification is equivalent to linear identification of the socalled Koopman operator. Instead of considering nonlinear system identi…
Network Reconstruction from Intrinsic Noise
David Hayden, Ye Yuan, Jorge Goncalves
This paper considers the problem of inferring an unknown network of dynamical systems driven by unknown, intrinsic, noise inputs. Equivalently we seek to identify direct causal dep…