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This work shows how the combination weights of diffusion strategies for adaptation and learning over networks can be chosen in order for the network mean-square-error performance to match that of an optimized centralized (or batch) solution. The results sh ...
Inference from data is of key importance in many applications of informatics. The current trend in performing such a task of inference from data is to utilise machine learning algorithms. Moreover, in many applications that it is either required or is pref ...
Modelling, dimensioning and performance analysis of optical backbone networks is the main concern of this thesis. Modelling consists in representing a network under a abstract form, simpler and easier to analyse, the model. Dimensioning is achieved when ne ...
We analyse deterministic aggregative games, with large but finite number of players, that are subject to both local and coupling constraints. Firstly, we derive sufficient conditions for the existence of a generalized Nash equilibrium, by using the theory ...
With the liberalization of the electricity market, the cross-boarder transactions have become more common but set up new problems due to the non-existence of a global interconnected network operator which would have a whole knowledge of such electrical sys ...
This paper presents a systematic computational study on the performance of distributed optimization in model predictive control (MPC). We consider networks of dynamically coupled systems, which are subject to input and state con- straints. The resulting MP ...
In this paper, the decentralized coordination of point-mass autonomous vehicles at intersections using navigation functions is considered. As main contribution, the inertia of the vehicles is taken into account to enable on-board energy optimization for cr ...
An epidemic spreading in a network calls for a decision on the part of the network members: They should decide whether to protect themselves or not. Their decision depends on the trade-off between their perceived risk of being infected and the cost of bein ...
Institute of Electrical and Electronics Engineers2013
Part I of this paper examined the mean-square stability and convergence of the learning process of distributed strategies over graphs. The results identified conditions on the network topology, utilities, and data in order to ensure stability; the results ...
This paper presents a network partitioning strategy for the optimal voltage control of Active Distribution Networks (ADNs) by means of Dispersed Energy Storage Systems (DESSs). The proposed partitioning is based on the concept of voltage sensitivity coeffi ...