Fig. 4
From: The applied principles of EEG analysis methods in neuroscience and clinical neurology
Summary of method selection for different data characteristics and application requirements. AR autoregressive, CFA ross-frequency analysis, CNN convolutional neural network, COH coherence, CORR correlation, CSD current source density, CSP common spatial patterns, EEG electroencephalography, EMD empirical mode decomposition, FFT fast Fourier transform, FOCUSS focal underdetermined system solution, GC granger causality, LDA linear discriminant analysis, LORETA low-resolution electromagnetic tomography, LSTM long short-term memory, MI mutual information, PLV/PLI phase lag value/index, RNN recurrent neural network, STFT short-time Fourier transform, SVM support vector machine, WT wavelet transform, WTC wavelet coherence, WVD Wigner-Ville distribution