Dynamic Bayesian Network
A dynamic Bayesian network (DBN) is a Bayesian network (BN) which relates variables to each other over adjacent time steps. History A dynamic Bayesian network (DBN) is often called a "two-timeslice" BN (2TBN) because it says that at any point in time T, the value of a variable can be calculated from the internal regressors and the immediate prior value (time T-1). DBNs were developed by Paul Dagum in the early 1990s at Stanford University's Section on Medical Informatics. Dagum developed DBNs to unify and extend traditional linear state-space models such as Kalman filters, linear and normal forecasting models such as ARMA and simple dependency models such as hidden Markov models into a general probabilistic representation and inference mechanism for arbitrary nonlinear and non-normal time-dependent domains. Today, DBNs are common in robotics, and have shown potential for a wide range of data mining applications. For example, they have been used in speech recognition, digi ...
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Réseau Bayésien Dynamique
The term réseau derives from a French word meaning "network". It may mean: *a network of fine lines on a glass plate, used in photographic telescopes to make a corresponding network on photographs of the stars: see Réseau plate *a system of weather stations under a single agency, or cooperating on common goals *an intelligence network as used by John Le Carré, in ''Tinker, Tailor, Soldier, Spy'', chapter 11. *the net in bobbin lace * SNCF TGV Réseau The SNCF TGV Réseau (TGV-R) is a TGV train built by Alstom between 1992 and 1996 for SNCF, the French national railway for use on high-speed TGV services. The Réseau trainsets are based on the earlier TGV Atlantique. The first Réseau () sets ...