Publication Date
2023
Document Type
Dissertation/Thesis
First Advisor
Polansky, Alan M.
Degree Name
M.S. (Master of Science)
Legacy Department
Department of Statistics and Actuarial Science
Abstract
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.
Recommended Citation
Rafael, Patrick B., "A State Space Modeling Approach to EEG Artifact Removal" (2023). Graduate Research Theses & Dissertations. 7845.
https://huskiecommons.lib.niu.edu/allgraduate-thesesdissertations/7845
Extent
88 pages
Language
en
Publisher
Northern Illinois University
Rights Statement
In Copyright
Rights Statement 2
NIU theses are protected by copyright. They may be viewed from Huskie Commons for any purpose, but reproduction or distribution in any format is prohibited without the written permission of the authors.
Media Type
Text
