Abstract #301357

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JSM 2003 Abstract #301357
Activity Number: 64
Type: Invited
Date/Time: Sunday, August 3, 2003 : 6:00 PM to 8:00 PM
Sponsor: General Methodology
Abstract - #301357
Title: Time-Frequency Discrimination of Nonstationary Processes Based on Wavelets
Author(s): Joseph E. Cavanaugh*+ and J. Wade Davis
Companies: University of Missouri, Columbia and University of Missouri, Columbia
Address: Dept. of Statistics, Columbia, MO, 65211-4100,
Keywords: discriminant analysis ; nonstationarity ; time series analysis ; wavelets
Abstract:

Techniques for time series discrimination have been employed in many different scientific areas. Applications include speech pattern recognition, the categorization of seismic records as originating from either nuclear explosions or earthquakes (Shumway 2003), the classification of cities to various climate regimes based on temperature patterns (Davis and Cavanaugh 2001), and the determination of different states of consciousness based on EEG readings (Gersch 1981). Since many time series exhibit nonstationary dynamics, a great need exists for discrimination procedures that exploit, rather than ignore, temporal frequency shifts. In this exhibit, we present a procedure based on wavelets for time-frequency discrimination of nonstationary processes. Our exhibit features an interactive element where the viewer may attempt to visually classify a series to one of several candidate populations. The populations are represented by sets of prototypical series. Since these same sets are used in constructing our discriminant rule, the viewer has access to the same information as our procedure. The classification capabilities of the viewer and the procedure may then be compared.

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