Continuous-time non-linear non-gaussian state-space modeling of electroencephalography with sequential Monte Carlo based estimation
Biomedical time series are non-stationary stochastic processes with hidden dynamics that can be modeled by state-space models (SSMs), and processing of which can be cast into optimal filtering problems for SSMs. The existing studies assume discrete-time linear Gaussian SSMs with estimation solved an...
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| Format: | Thesis |
| Language: | English |
| Published: |
2012
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| Online Access: | http://eprints.utm.my/id/eprint/30694/5/TingCheeMingPFS2012.pdf |
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