Linear dynamic models for classification of single-trial EEG

• Main Authors: Samdin, S. Balqis, Ting, Chee-Ming, Salleh, Sh-Hussain, Ariff, A.K., Noor, A. B. Mohd
• Format: Conference or Workshop Item
• Published: 2013
• Subjects: QH Natural history
• Online Access: http://eprints.utm.my/id/eprint/51144/; http://apps.webofknowledge.com.ezproxy.utm.my/full_record.do?product=WOS&search_mode=GeneralSearch&qid=6&SID=R2bDzISyUVdV24ggHTF&page=1&doc=1

This paper investigates the use of linear dynamic models (LDMs) to improve classification of single-trial EEG signals. Existing dynamic classification of EEG uses discrete-state hidden Markov models (HMMs) based on piecewise-stationary assumption, which is inadequate for modeling the highly non-stat...