Spectral Decomposition of EEG Intervals Using Walsh and Fourier Transforms

This paper presents a comparison of the use of features derived from Walsh and Fourier transforms for classification of short segments of EEG data. The result was that features obtained from Fourier transforms produced consistently better classification results than Walsh function-derived features.

[1]  Warren D. Smith.  Walsh Versus Fourier Estimators of the EEG Power Spectrum , 1981, IEEE Transactions on Biomedical Engineering.

[2]  John R. Bourne,et al.  Syntactic Analysis of the Electroencephalogram , 1979, IEEE Transactions on Systems, Man, and Cybernetics.

[3]  Dietrich Lehmann,et al.  Evaluation of Methods for Three-Dimensional Localization of Electrical Sources in the Human Brain , 1978, IEEE Transactions on Biomedical Engineering.

[4]  L T Andrews,et al.  Real-time analysis of EEG using Walsh transforms. , 1978, Computers in biology and medicine.

[5]  M R Schneider,et al.  A multistage process for computing virtual dipolar sources of EEG discharges from surface information. , 1972, IEEE transactions on bio-medical engineering.

[6]  N. M. Blachman.  Sinusoids versus Walsh functions , 1974 .

[7]  D. C. Lai,et al.  Walsh Spectral Estimates with Applications to the Classification of EEG Signals , 1980, IEEE Transactions on Biomedical Engineering.

[8]  S. Butler,et al.  The localization of equivalent dipoles of EEG sources by the application of electrical field theory. , 1975, Electroencephalography and clinical neurophysiology.