Sequential Bayesian Estimation for Adaptive Classification

Sequential Bayesian Estimation for Adaptive Classification

This paper proposes a robust algorithm to adapt a model for EEG signal classification using a modified Extended Kalman Filter (EKF). By applying Bayesian conjugate priors and marginalising the parameters, we can avoid the needs to estimate the covariances of the observation and hidden state noises....

Полное описание

Библиографические подробности
Главные авторы:	Yoon, J, Roberts, S, Dyson, M, Can, J, IEEE
Формат:	Conference item
Опубликовано:	2008

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