DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | Kim, Kee-Eung | - |
dc.contributor.advisor | 김기응 | - |
dc.contributor.author | Park, Jae-Young | - |
dc.contributor.author | 박재영 | - |
dc.date.accessioned | 2011-12-13T06:09:13Z | - |
dc.date.available | 2011-12-13T06:09:13Z | - |
dc.date.issued | 2010 | - |
dc.identifier.uri | http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=455244&flag=dissertation | - |
dc.identifier.uri | http://hdl.handle.net/10203/34935 | - |
dc.description | 학위논문(석사) - 한국과학기술원 : 전산학과, 2010.08, [ (A) POMDP approach to p300-based brain-computer interfaces], [ vi, 35 p. ] | - |
dc.description.abstract | Most of the previous work on non-invasive brain-computer interfaces (BCIs) has been focused on feature extraction and classification algorithms to achieve high performance for the communication between the brain and the computer. While significant progress has been made in the lower layer of the BCI system, the issues in the higher layer have not been sufficiently addressed. Existing P300-based BCI systems, for example the P300 speller, use a random order of stimulus sequence for eliciting P300 signal for identifying users’ intentions. This paper is about computing an optimal sequence of stimulus in order to minimize the number of stimuli, hence improving the performance. To accomplish this, we model the problem as a partially observable Markov decision process (POMDP), which is a model for planning in partially observable stochastic environments. Through simulation and human subject experiments, we show that our approach achieves a significant performance improvement in terms of the success rate and the bit rate. | eng |
dc.language | eng | - |
dc.publisher | 한국과학기술원 | - |
dc.subject | Brain-Computer Interfaces | - |
dc.subject | Partially Observable Markov Decision Processes (POMDPs) | - |
dc.subject | Reinforcement Learning | - |
dc.subject | Machine Learning | - |
dc.subject | P300 | - |
dc.subject | P300 | - |
dc.subject | 뇌-컴퓨터 인터페이스 | - |
dc.subject | 부분 관찰 마르코프 의사 결정 모델 | - |
dc.subject | 강화학습 | - |
dc.subject | 기계학습 | - |
dc.title | (A) POMDP approach to p300-based brain-computer interfaces | - |
dc.title.alternative | 부분 관찰 마르코프 의사 결정 모델을 이용한 P300 기반 뇌-컴퓨터 인터페이스 | - |
dc.type | Thesis(Master) | - |
dc.identifier.CNRN | 455244/325007 | - |
dc.description.department | 한국과학기술원 : 전산학과, | - |
dc.identifier.uid | 020084054 | - |
dc.contributor.localauthor | Kim, Kee-Eung | - |
dc.contributor.localauthor | 김기응 | - |
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