References of "Proverbio, Daniele 50034360"
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See detailInitialisation of Deep Brain Stimulation Parameters with Multi-objective Optimisation Using Imaging Data
Baniasadi, Mehri UL; Husch, Andreas UL; Proverbio, Daniele UL et al

in Bildverarbeitung für die Medizin 2022 (2022)

Following the deep brain stimulation (DBS) surgery, the stimulation parameters are manually tuned to reduce symptoms. This procedure can be timeconsuming, especially with directional leads. We propose an ... [more ▼]

Following the deep brain stimulation (DBS) surgery, the stimulation parameters are manually tuned to reduce symptoms. This procedure can be timeconsuming, especially with directional leads. We propose an automated methodology to initialise contact configurations using imaging techniques. The goal is to maximise the electric field on the target while minimising the spillover, and the electric field on regions of avoidance. By superposing pre-computed electric fields, we solve the optimisation problem in less than a minute, much more efficient compared to finite element methods. Our method offers a robust and rapid solution, and it is expected to considerably reduce the time required for manual parameter tuning. [less ▲]

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See detailAlmost global convergence to practical synchronization in the generalized Kuramoto model on networks over the n-sphere
Markdahl, Johan UL; Proverbio, Daniele UL; Mi, La et al

in Communications Physics (2021), 4

From the flashing of fireflies to autonomous robot swarms, synchronization phenomena are ubiquitous in nature and technology. They are commonly described by the Kuramoto model that, in this paper, we ... [more ▼]

From the flashing of fireflies to autonomous robot swarms, synchronization phenomena are ubiquitous in nature and technology. They are commonly described by the Kuramoto model that, in this paper, we generalise to networks over n-dimensional spheres. We show that, for almost all initial conditions, the sphere model converges to a set with small diameter if the model parameters satisfy a given bound. Moreover, for even n, a special case of the generalized model can achieve phase synchronization with nonidentical frequency parameters. These results contrast with the standard n = 1 Kuramoto model, which is multistable (i.e., has multiple equilibria), and converges to phase synchronization only if the frequency parameters are identical. Hence, this paper shows that the generalized network Kuramoto models for n ≥ 2 displays more coherent and predictable behavior than the standard n = 1 model, a desirable property both in flocks of animals and for robot control. [less ▲]

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See detailAssessing the robustness of decentralized gathering: a multi‐agent approach on micro‐biological systems
Proverbio, Daniele UL; Gallo, Luca; Passalacqua, Barbara et al

in Swarm Intelligence (2020), 14

Adopting a multi-agent systems paradigm, we developed, tested and exploited a computational testbed that simulates gathering features of the social amoeba Dictyostelium discoideum. It features a tailored ... [more ▼]

Adopting a multi-agent systems paradigm, we developed, tested and exploited a computational testbed that simulates gathering features of the social amoeba Dictyostelium discoideum. It features a tailored design and implementation to manage discrete simulations with autonomous agents on a microscopic scale, thus focusing on their social behavior and mutual interactions. Hence, we could assess the behavioral conditions under which decentralized gathering could occur. We investigated the dependence of the model dynamics on the main physical variables, namely density and number of amoebas, gaining indications that the process strongly depends on both. This result integrates previous researches, where density is identified as the sole relevant variable. We determined a high-density and high-numerosity region where assuming a scale-free behavior is safe. We also estimated the systematic uncertainties arising from a number of amoebas off the scale-free region, when coping with limited computational resources. Finally, we probed the robustness of the simulated gathering process against both extrinsic and intrinsic noise sources. [less ▲]

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See detailRobust synchronization of heterogeneous robot swarms on the sphere
Markdahl, Johan UL; Proverbio, Daniele UL; Goncalves, Jorge UL

in 2020 59th IEEE Conference on Decision and Control (CDC) (2020)

Synchronization on the sphere is important to certain control applications in swarm robotics. Of recent interest is the Lohe model, which generalizes the Kuramoto model from the circle to the sphere. The ... [more ▼]

Synchronization on the sphere is important to certain control applications in swarm robotics. Of recent interest is the Lohe model, which generalizes the Kuramoto model from the circle to the sphere. The Lohe model is mainly studied in mathematical physics as a toy model of quantum synchronization. The model makes few assumptions, wherefore it is well-suited to represent a swarm. Previous work on this model has focused on the cases of complete and acyclic networks or the homogeneous case where all oscillator frequencies are equal. This paper concerns the case of heterogeneous oscillators connected by a non-trivial network. We show that any undesired equilibrium is exponentially unstable if the frequencies satisfy a given bound. This property can also be interpreted as a robustness result for small model perturbations of the homogeneous case with zero frequencies. As such, the Lohe model is a good choice for control applications in swarm robotics. [less ▲]

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