A comparison of mental arithmetic performance in time and frequency domains.

ABSTRACT: The Heisenberg-Gabor uncertainty principle defines the limits of information resolution in both time and frequency domains. The limit of resolution discloses unique properties of a time series by frequency decomposition. However, classical methods such as Fourier analysis are limited by spectral leakage, particularly in longitudinal data with shifting periodicity or unequal intervals. Wavelet transformation provides a workable compromise by decomposing the signal in both time and frequency through translation and scaling of a basis function followed by correlation or convolution with the original signal. This study aimed to compare the accuracy of predictive models in mental arithmetic in time and frequency domains. Analysis of the author's response time at mental arithmetic using a soroba

SUBMITTER: Abdul-Rahman A 

PROVIDER: S-EPMC9478896 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature