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- W2359856570 abstract "The research of brain-computer interface attracts more and more interests,especially the classification and decoding of nerval activity is most important.This paper uses relevance vector machine algorithm to classify the firing rates from small populations of neurons in primary motor cortex.It uses the output of classifier to recursively infer nerval state and hand kinematics conditioned on neural firing rates.Experiments show that the relevance vector machine algorithm is suited for the classification and decoding of nerval activity,and the performance of relevance vector machine is better than the popular support vector machine and information vector machine." @default.
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- W2359856570 date "2009-01-01" @default.
- W2359856570 modified "2023-09-23" @default.
- W2359856570 title "Nerval Activity Classification and Decoding Based on Relevance Vector Machine" @default.
- W2359856570 hasPublicationYear "2009" @default.
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