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F. Garofalo

Researcher at University of Naples Federico II

Publications -  33
Citations -  477

F. Garofalo is an academic researcher from University of Naples Federico II. The author has contributed to research in topics: Nonlinear system & Robust control. The author has an hindex of 8, co-authored 33 publications receiving 453 citations.

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Journal ArticleDOI

Brief paper: Novel decentralized adaptive strategies for the synchronization of complex networks

TL;DR: Time-varying feedback coupling gains are considered, whose gradient is a function of the local synchronization error over each edge in the network, and it is shown that, under appropriate conditions, the strategy is indeed successful in guaranteeing the achievement of a common synchronous evolution for all oscillators in thenetwork.
Journal ArticleDOI

Robust and quadratic stability via polytopic set covering

TL;DR: Two main algorithms are presented: the first one performs a covering of a given function by a polytope and works under quite general assumptions on the nature of the function; the second one is iterative and allows us to improve at will the goodness of the covering.
Proceedings ArticleDOI

Robust output feedback active queue management control in TCP networks

TL;DR: An appropriate robust H/sup /spl infin// controller for time-delay systems is proposed and hence used to design a suitable AQM control scheme and a robust observer is used to estimate online the transmission window resulting in a novel output feedback stabilization scheme for AQM.
Proceedings ArticleDOI

A robust approach to active queue management control in networks

TL;DR: The aim is to stabilize the delay differential equations model of TCP (transmission control protocol) behavior and introduce a robust observer to estimate online the transmission window resulting in a window-based congestion control scheme.
Proceedings ArticleDOI

Small world effects in networks: an engineering interpretation

TL;DR: It is shown that the performance of a communication network is indeed affected by the presence or absence of small world effects, and the link between these effects and the average throughput and delivery time on the network is established and assessed through numerical simulations.