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Sequential Bayesian estimation for adaptive classification

Yoon, JW and Roberts, SJ and Dyson, M and Gan, JQ (2008) Sequential Bayesian estimation for adaptive classification. In: UNSPECIFIED, ? - ?.

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Abstract

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. In addition, Laplace approximation is employed in our model to approximate non-Gaussian distributions as Gaussians. ©2008 IEEE.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Additional Information: Published proceedings: IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Users 161 not found.
Date Deposited: 15 Dec 2012 12:31
Last Modified: 23 Jan 2019 00:15
URI: http://repository.essex.ac.uk/id/eprint/4182

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