activity
20152021
most citedStructural Systems Theory: an overview of the last 15 years

14 citations · 23 across the 9 of their papers we have counts for

collaborators

16 papers

eess.SY20211 cited

Minimum Structural Sensor Placement for Switched Linear Time-Invariant Systems and Unknown Inputs

Emily A. Reed, Guilherme Ramos, Paul Bogdan +1

In this paper, we study the structural state and input observability of continuous-time switched linear time-invariant systems and unknown inputs. First, we provide necessary and s…

math.OC20211 cited

A scalable distributed dynamical systems approach to compute the strongly connected components and diameter of networks

Emily A. Reed, Guilherme Ramos, Paul Bogdan +1

Finding strongly connected components (SCCs) and the diameter of a directed network play a key role in a variety of discrete optimization problems, and subsequently, machine learni…

math.OC2021

Discrete-Time Fractional-Order Dynamical Networks Minimum-Energy State Estimation

Sarthak Chatterjee, Andrea Alessandretti, A. Pedro Aguiar +1

Fractional-order dynamical networks are increasingly being used to model and describe processes demonstrating long-term memory or complex interlaced dependencies amongst the spatia…

math.OC2021

On Learning Discrete-Time Fractional-Order Dynamical Systems

Sarthak Chatterjee, Sérgio Pequito

Discrete-time fractional-order dynamical systems (DT-FODS) have found innumerable applications in the context of modeling spatiotemporal behaviors associated with long-term memory.…

math.OC202014 cited

Structural Systems Theory: an overview of the last 15 years

Guilherme Ramos, A. Pedro Aguiar, Sergio Pequito

In this paper, we provide an overview of the research conducted in the context of structural systems since the latest survey by Dion et al. in 2003. We systematically consider all…

cs.LG20202 cited

Equilibrium Propagation for Complete Directed Neural Networks

Matilde Tristany Farinha, Sérgio Pequito, Pedro A. Santos +1

Artificial neural networks, one of the most successful approaches to supervised learning, were originally inspired by their biological counterparts. However, the most successful le…