Praktische Aspekte der Parameterreduktion in EEG-Spektren

Hinrichs, Hermann

doi:10.1007/978-3-642-81034-3_32

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1976

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“…Parameter reduction starting from a spectrum and resulting in a small set of parameters that contain the essential information has been tried in many ways. The results, however, are not very satisfactory, except may be Hjorth's NSD-parameters (H:rNRIOHS [2]). This and rule c) are the reasons why we took a set of 25 rather conventional parameters per spectrum as a starting point for our investigations:…”

Section: Data Investigatedmentioning

confidence: 87%

Distribution of Variables Extracted from Spectral EEG-Analysis

Ferber¹,

Eichholz²

1976

Methods Inf Med

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For 1000 variables extracted from auto- and cross-spectra of two 12-channel montages, the empirical density function is investigated. Only a small group of them may be considered to have a univariate normal distribution. Another important group including the absolute and the relative power in the four classical frequency bands has distribution functions that may be more or less accurately approximated by gamma-type functions.A third group including some of the peak frequencies shows distribution functions with two peaks not assignable to any natural classification of the EEG.The power of discrimination between the four samples is investigated for each variable by means of Bayes-classification and by a quasi-Kolmogorov-statistic. Its quality is demonstrated using linear discriminant analysis.Correlations were computed to complete basic statistical information.

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Section: Data Investigatedmentioning

confidence: 87%