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EN
Multicast realises the data delivering to a group of destinations simultaneously while using the minimum network resources. The first implementation of multicasting has been built using specialized multicast routers and is well known as IP Multicast. Such a network comprises some drawback including complex addressing and routing scheme, it requires the deployment of special routers that are rather expensive and finally, there has not been proposed a reasonable business model regarding cross-providers multicast realization. Thereby, for the past few years, a new interest in delivering multicast traffic has arisen and some multicast systems defined for end-hosts overlay network have been successfully proposed. Overlay multicast implements a multicast technique at the top of computer networks and creates a virtual topology of clients which duplicate packets and maintain a multicast structure. This overlay structure forms an independent layer with logical links between the nodes without the knowledge about the underlaying topology. In the work we take a look at flow cost minimization of multicast stream in a system which combines the advantages of overlays and underlaying network awareness. This papers presents three independent linear-based models aimed at optimization of multicast tree topology and its network level unicast realization. The proposed formulations can be applied for deriving either lower bound of flows costs in existing systems or for designing new cooperative multilayer protocols for effective multicast transmission.
PL
W artykule przedstawiono neuronowe estymatory zmiennych stanu układu napędowego z połączeniem sprężystym do odtwarzania momentu skrętnego i prędkości maszyny roboczej. Omówiono proces projektowania sieci neuronowych oraz optymalizacji ich struktury przy wykorzystaniu metody Optimal Brain Surgeon (OBS). Zaprojektowane estymatory zostały przetestowane w badaniach symulacyjnych z punktu widzenia dokładności odtwarzania zmiennych stanu. Oceniono również wrażliwość zoptymalizowanych estymatorów na zmiany mechanicznej stałej czasowej napędu.
EN
The neural state estimators for state variables of the drive system with elastic coupling are discussed and demonstrated in the paper. These estimators are used for the reconstruction of the load side speed and torsional torque of the elastic drive. The design process of neural estimators' design and their optimization using the Optimal Brain Surgeon (OBS) method was presented in details. The developed neural estimators are tested in simulation from the point of view of the quality of state variable reconstruction. The robustness of the optimized estimators is tested under changes of the mechanical time constant of the load side. The estimation quality is evaluated.
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