TitleWavelets to detect ultradian rhythms
NameEgen, Dennis (author), Ramaswami, Suneeta (chair), Hong, Dawei (internal member), Rutgers University, Camden Graduate School,
DescriptionUntil the mid-1990s limitations in signal processing did not allow us to easily analyze frequency and temporal components of a given non-stationary signal at the same time. Wavelet transforms allow researchers to analyze the frequency components of a signal while not losing information about the time those components occur. In this work we apply these Wavelet techniques in the analysis of EEG data, particularly, to identify ultradian rhythms in rats. Our work presents a framework for computational analysis of EEG data for the detection of these ultradian rhythms.
NoteIncludes bibliographical references
Noteby Dennis Egen
CollectionCamden Graduate School Electronic Theses and Dissertations
Organization NameRutgers, The State University of New Jersey
RightsThe author owns the copyright to this work.