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A State Space Modeling Approach To Eeg Artifact Removal, Patrick B. Rafael
A State Space Modeling Approach To Eeg Artifact Removal, Patrick B. Rafael
Graduate Research Theses & Dissertations
In this work, a state space modeling approach is applied to an Electroencephalography(EEG) recording for the purpose of artifact removal, and is compared against Independent Components Analysis (ICA), the current gold standard. Issues of model identifiability are touched on, and Hamiltonian Monte Carlo (HMC) is used to estimate a linear non-Gaussian state space model. Results show that estimating such a model is a nontrivial matter, and the full utility of the state space approach remains to be demonstrated.