Institute of Information Theory and Automation

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Bibliography

Journal Article

Bayesian estimation of traffic lane state

Nagy Ivan, Kárný Miroslav, Nedoma Petr, Voráčová Š.

: International Journal of Adaptive Control and Signal Processing vol.17, 1 (2003), p. 51-65

: CEZ:AV0Z1075907

: GA102/03/0049, GA ČR, IBS1075351, GA AV ČR

: mixture models, estimation, Bayesian approach

: http://library.utia.cas.cz/prace/20030021.ps

(eng): The paper deals with modelling and estimation by a model described as a mixture of distributions. In this case, the exact application of the Bayes theory adopted is not feasible and its approximation is used. The general algorithm is specified for mixtures with components from exponential family. The theory is demonstrated on estimation of the basic relation between density and intensity of traffic flow in a single point of a vehicular communication and it can provides us with state classification.

: 09I

: BB

2019-01-07 08:39