Research Article
Entropy-Based Pattern Learning Based on Singular Spectrum Analysis Components for Assessment of Physiological Signals
Table 10
Comparison results of the identification accuracies for entropy-based pattern learning to identify specific biosignal patterns from EEG, EMG, and RR-interval signals with and without SSA components representation. For pattern learning task #1, #2, and #3, FuzzyEn is used as the entropy features for experimental analysis, the SVM is used as pattern classifier and LOOCV is used as the cross-validation strategy. DimIF, dimension of input features.
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