A consensus model combines statistical methods with signal processing to create a better picture of the family of related signals. In this thesis, we will consider 32 signals produced by a single electroencephalogram (EEG) recording session. The consensus model will be produced by using the S-Transform of the individual signals and then normalized to unit energy. A bootstrapping process is used to produce a consensus spectrum. This leads to the consensus model via the inverse S-Transform of the consensus spectrum. The method will be applied to both a control and experimental EEG to show how the results can be used in clinical settings to analyze experimental outcomes.
| Identifer | oai:union.ndltd.org:ETSU/oai:dc.etsu.edu:etd-2617 |
| Date | 05 May 2012 |
| Creators | Young, Andrew Coady |
| Publisher | Digital Commons @ East Tennessee State University |
| Source Sets | East Tennessee State University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Electronic Theses and Dissertations |
| Rights | Copyright by the authors. |
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