**Abbreviations**

A

AB; AdaBoost, ANFIS; Adaptive neuro-fuzzy inference system, ANFN; Adaptive neural fuzzy network, ANN; Artificial Neural Network, ApEn; Approximate entropy, AR; Autoregressive model, ARMA; Autoregressive moving average model.

B

BayesNet; Bayes networks; BD; Blancket dimension, BP; Backpropagation, BPNN; Back propagation neural network, BRBP; Bayesian regularization backpropagation, BSVM; Bagged support vector machine, BT; Bagging tree. C

CD; Correlation dimension, CM; Co-occurrence matrix, CNN; Convolutional neural network, CVANN; Complex-valued neural networks, CWPS; Continuous wavelet power spectra, CWT; Continuous wavelet transform.

D

DA; Discriminant analysis, DCT; Discrete cosine transform, DT; Decision tree, DTCWT; Dual-tree complex wavelet transformation, DWPS; Discrete wavelet power spectra, DWT; Discrete wavelet transform.

E

ECOC; Error-correction output codes, EFD; Equal frequency discretization, ELM; Extreme learning machine, EMA; Expectation–maximization algorithm, EMD; Empirical Mode Decomposition, ENSC; Ensemble noise-aware signal combination; ESN; Echo state network, EWD; Equal width discretization, ExpEn; Exponential energy.

F

FCBFA; Fast Correlation Based Filter algorithm, FD; Fractal dimension, fDistEn; Fuzzy distribution entropy, FE; Fuzzy entropy, FFANN; Feed-forward

### *Is EEG a Useful Examination Tool for Diagnosis of Epilepsy and Comorbid Psychiatric Disorders? DOI: http://dx.doi.org/10.5772/intechopen.94352*

artificial neural network, FFBPNN; Feed forward back-propagation neural network, FI; Fractal intercept, FPCA; Functional principal component analysis, FSC; Fuzzy Sugeno Classifier, FT; Functional trees.

G

GA; Genetic algorithm, GAFDS; Genetic algorithm-based frequency-domain feature search, GASVM; Genetic algorithm support vector machine, GARCH; Generalized autoregressive conditional heteroscedasticity, GDM; Gradient descent method, GEO; Gradient energy operator, GMM; Gaussian mixture model, GP; Genetic programming, GRA; Gray relational analysis.

H

HE; Hurst exponent, HFD; Higuchi fractal dimension, H-MSVM; Hierarchical multi-class support vector machine, HOA; Higher order autocovariance, HOS; Higher order spectra, HSFV; Hybrid-selection-feature vector.

I

ICA; Independent component analysis, ICNC; Inverse correlation network coupling, IShE; Indirect shannon entropy.

K

KMA; K-means algorithm, KMC; K-means clustering, KNN; K-nearest neighbor, KPCA; Kernel principal component analysis, KSE; Kolmogorov Sinai entropy. L

LE; Lyapunov exponent, LBP; Local binary pattern, LEEn; Log energy entropy, LDA; Linear discriminant analysis, LLS; Linear least squares, LMA; Levenberg– marquardt algorithm, LMD; Local mean decomposition, LME; Laws mask energy, LNDP; Local neighbor descriptive pattern, LNGP; Local neighbor gradient pattern, LR; Logistic regression, LSP; Local speed pattern, LSP; Local senary pattern, LSPA; Lorenz scatter plot area, LS-SVM; Last squares support vector machine, LSVM; Linear support vector machine.

M

ME; Mixture of experts, MFDFA; MKM; Multi-scale K-means algorithm, Multifractal detrended fluctuation analysis, MLP; Multilayer perceptron, MME; Modified mixture of experts, MN; Minimum-Norm, MPE; Multiscale permutation entropy, MPEr; Multiscale permutation renyi entropy, MRF; Markov random field, MSVM; Multiclass support vector machine, MUSIC; Multiple signal classification. N

NB; Naive Bayes, NE; Norm entropy, NEO; Nonlinear energy operator, NN; Nearest neighbor, NN; Neural network, NPE; Nonlinear prediction error, NSVM; Nonlinear support vector machine.

O

OC; Omega complexity, 1D-LBP; One-dimensional local binary pattern, 1D-LGP; One-dimensional local gradient pattern, 1D-TP; One-dimensional ternary patterns.

P

PCA; Principal component analysis, PE; Permutation entropy, PM; Pisarenko method, PNN; Probabilistic neural network, PP; Poincare plot, PS; Phase synchrony; PSD; Power spectral density, PSVM; Polynominal support vector machine. Q

QDA; Quadratic discriminant analysis, QLDA; Quadratic linear discriminant analysis, QSVM; Quadratic support vector machine.

R

RBFSVM; Radial basis function support vector machine, RE; Renyi entropy, REN; Recurrent elman neural network, RF; Random trees, RLM; Run length matrix, RNN; Recurrent neural network, RP; Recurrence plots, RQA; Recurrence quantification analysis.

S

SampEn; Sample entropy, SE; Shannon entropy, SELM; Sparse extreme learning machine, SFFS-LDA; Sequential floating forward search with linear discriminant analysis method, SLMC; Spatial linear mode complexity, SSE; Shannon spectral entropy, ST; Stockwell transform, STFT; Short time fourier transform, SPWVD; Smoothed pseudo-wigner-ville distribution, SVM; Support vector machine, SWLNGP; Symmetrically weighted local neighbor gradient pattern.

T

TEE; Temporal energy entropy, TQWT; Tunable Q-factor wavelet transform, TRA; Time reversal asymmetry.

V

VGA; Visibility graph algorithm.

W

WEE; Wavelet energy entropy, WPE; Wavelet packet energy, WPE; Weighted permutation Entropy, WPD; Wavelet packet decomposition.
