Abstract
The accuracy and computational speed of three algorithms (spectral analysis, period analysis, and period amplitude analysis) for the extraction of spectral estimates from time-series data are empirically evaluated in the context of a neuropsychological experiment that requires estimates of power in the standard electroencephalographic frequency bands.
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This research was supported by the Advanced Research Projects Agency of the Department of Defense and was monitored by the Off Research under Contract N0001-70-C-0350. Additional on-line computer processing for data analysis was provided by the Center for Computer-based Behavioral Studies under Contract F30602-70-C0016 with Advanced Research Projects Agency of the Department of Defense.
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Beatty, J., Figueroa, C. Period analytic algorithms for the estimation of selected spectral properties of short segments of EEG data. Behavior Research Methods & Instrumentation 6, 293–295 (1974). https://doi.org/10.3758/BF03200346
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DOI: https://doi.org/10.3758/BF03200346