%Aigaion2 BibTeX export from Idiap Publications
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@INPROCEEDINGS{silviac03hmm,
         author = {Chiappa, Silvia and Bengio, Samy},
       projects = {Idiap},
          title = {HMM and IOHMM Modeling of EEG Rhythms for Asynchronous BCI Systems},
      booktitle = {European Symposium on Artificial Neural Networks {ESANN}},
           year = {2004},
    institution = {IDIAP},
           note = {IDIAP-RR 03-49},
       crossref = {silviac03hmm:rr-03-49},
       abstract = {We compare the use of two Markovian models, HMMs and IOHMMs, to discriminate between three mental tasks for brain computer interface systems using an asynchronous protocol. We show that IOHMMs outperform HMMs but that, probably due to the lack of any prior information on the state dynamics, no practical advantage in the use of these models over their static counterparts is obtained.},
            pdf = {https://publications.idiap.ch/attachments/reports/2004/silviac_esann04.pdf},
     postscript = {ftp://ftp.idiap.ch/pub/reports/2004/silviac_esann04.ps.gz},
ipdmembership={learning},
}



crossreferenced publications: 
@TECHREPORT{silviac03hmm:rr-03-49,
         author = {Chiappa, Silvia and Bengio, Samy},
       projects = {Idiap},
          title = {HMM and IOHMM Modeling of EEG Rhythms for Asynchronous BCI Systems},
           type = {Idiap-RR},
         number = {Idiap-RR-49-2003},
           year = {2003},
    institution = {IDIAP},
           note = {Accepted for publication in ESANN 2004},
       abstract = {We compare the use of two Markovian models, HMMs and IOHMMs, to discriminate between three mental tasks for brain computer interface systems using an asynchronous protocol. We show that IOHMMs outperform HMMs but that, probably due to the lack of any prior information on the state dynamics, no practical advantage in the use of these models over their static counterparts is obtained.},
            pdf = {https://publications.idiap.ch/attachments/reports/2003/rr03-49.pdf},
     postscript = {ftp://ftp.idiap.ch/pub/reports/2003/rr03-49.ps.gz},
ipdmembership={learning},
}