3 citations · 3 across the 3 of their papers we have counts for
10 papers · 1 filter
Node-Adaptive Regularization for Graph Signal Reconstruction
Maosheng Yang, Mario Coutino, Geert Leus +1
A critical task in graph signal processing is to estimate the true signal from noisy observations over a subset of nodes, also known as the reconstruction problem. In this paper, w…
Online Time-Varying Topology Identification via Prediction-Correction Algorithms
Alberto Natali, Mario Coutino, Elvin Isufi +1
Signal processing and machine learning algorithms for data supported over graphs, require the knowledge of the graph topology. Unless this information is given by the physics of th…
Topology-Aware Joint Graph Filter and Edge Weight Identification for Network Processes
Alberto Natali, Mario Coutino, Geert Leus
Data defined over a network have been successfully modelled by means of graph filters. However, although in many scenarios the connectivity of the network is known, e.g., smart gri…
Joint blind calibration and time-delay estimation for multiband ranging
Tarik Kazaz, Mario Coutino, Gerard J. M. Janssen +1
In this paper, we focus on the problem of blind joint calibration of multiband transceivers and time-delay (TD) estimation of multipath channels. We show that this problem can be f…
State-Space Based Network Topology Identification
Mario Coutino, Elvin Isufi, Takanori Maehara +1
In this work, we explore the state-space formulation of network processes to recover the underlying structure of the network (local connections). To do so, we employ subspace techn…
State-Space Network Topology Identification from Partial Observations
Mario Coutino, Elvin Isufi, Takanori Maehara +1
In this work, we explore the state-space formulation of a network process to recover, from partial observations, the underlying network topology that drives its dynamics. To do so,…