activity
20082021
most citedLarge-signal stability conditions for semi-quasi-Z-source inverters: switched and averaged models

12 citations · 25 across the 11 of their papers we have counts for

collaborators

17 papers

eess.SY2021

Discrete-Time Consensus Networks: Scalability, Grounding and Countermeasures

Yamin Yan, Sonja Stüdli, Maria M. Seron +1

We investigate the disruption of discrete-time consensus problems via grounding. Loosely speaking, grounding a network occurs if the state of one agent no longer responds to inputs…

cs.IT2020★ 1 cited

Joint Resource Allocation to Minimize Execution Time of Federated Learning in Cell-Free Massive MIMO

Tung T. Vu, Duy T. Ngo, Hien Quoc Ngo +3

Due to its communication efficiency and privacy-preserving capability, federated learning (FL) has emerged as a promising framework for machine learning in 5G-and-beyond wireless n…

eess.SY2020★ 1 cited

Scalability in nonlinear network systems affected by delays and disturbances

Shihao Xie, Giovanni Russo, Richard Middleton

This paper is concerned with the study of scalability in nonlinear heterogeneous networks affected by communication delays and disturbances. After formalizing the notion of scalabi…

eess.SY2020★ 3 cited

Analysis of Attack via Grounding and Countermeasures in Discrete-Time Consensus Networks

Yamin Yan, Sonja Stuedli, Maria M. Seron +1

We investigate the disruption of discrete-time consensus problems via grounding. Loosely speaking, grounding a network occurs if the state of one agent no longer responds to inputs…

eess.SP2019

Cell-Free Massive MIMO for Wireless Federated Learning

Tung T. Vu, Duy T. Ngo, Nguyen H. Tran +3

This paper proposes a novel scheme for cell-free massive multiple-input multiple-output (CFmMIMO) networks to support any federated learning (FL) framework. This scheme allows each…

math.OC2019

Scalability and Fragility in Bounded-Degree Consensus Networks

Emma Tegling, Richard H. Middleton, Maria M. Seron

We investigate the performance of linear consensus algorithms subject to a scaling of the underlying network size. Specifically, we model networked systems with ord…