Degree Name

MS (Master of Science)

Program

Mathematical Sciences

Date of Award

5-2012

Committee Chair or Co-Chairs

Jeff Knisley

Committee Members

Michele Joyner, Robert B. Gardner, Debra J. Knisley

Abstract

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.

Document Type

Thesis - Open Access

Copyright

Copyright by the authors.

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