Adaptive BCI based on variational Bayesian Kalman filtering: an empirical evaluation.
This paper proposes the use of variational Kalman filtering as an inference technique for adaptive classification in a brain computer interface (BCI). The proposed algorithm translates electroencephalogram segments adaptively into probabilities of cognitive states. It, thus, allows for nonstationari...
| Main Authors: | , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
2004
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