activity
20132024
most citedEfficient Compressive Sampling of Spatially Sparse Fields in Wireless Sensor Networks

3 citations · 5 across the 5 of their papers we have counts for

collaborators

5 papers

q-bio.NC2024

Community Detection from Multiple Observations: from Product Graph Model to Brain Applications

Tiziana Cattai, Gaetano Scarano, Marie-Constance Corsi +2

This paper proposes a multilayer graph model for the community detection from multiple observations. This is a very frequent situation, when different estimators are applied to inf…

eess.SP2021

Multiscale Anisotropic Harmonic Filters on non Euclidean domains

Francesco Conti, Gaetano Scarano, Stefania Colonnese

This paper introduces Multiscale Anisotropic Harmonic Filters (MAHFs) aimed at extracting signal variations over non-Euclidean domains, namely 2D-Manifolds and their discrete repre…

q-bio.NC2020★ 2 cited

Improving J-divergence of brain connectivity states by graph Laplacian denoising

Tiziana Cattai, Gaetano Scarano, Marie-Constance Corsi +3

Functional connectivity (FC) can be represented as a network, and is frequently used to better understand the neural underpinnings of complex tasks such as motor imagery (MI) detec…

q-bio.NC2019

Phase/amplitude synchronization of brain signals during motor imagery BCI tasks

Tiziana Cattai, Stefania Colonnese, Marie-Constance Corsi +3

The extraction of brain functioning features is a crucial step in the definition of brain-computer interfaces (BCIs). In the last decade, functional connectivity (FC) estimators ha…

cs.IT2013★ 3 cited

Efficient Compressive Sampling of Spatially Sparse Fields in Wireless Sensor Networks

Stefania Colonnese, Roberto Cusani, Stefano Rinauro +2

Wireless sensor networks (WSN), i.e. networks of autonomous, wireless sensing nodes spatially deployed over a geographical area, are often faced with acquisition of spatially spars…