Classification of Sleep Patterns by Means of Markov Modeling and Correspondence Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Unsupervised Optimal Fuzzy Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Validity Measure for Fuzzy Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
Unsupervised classification and adaptive definition of sleep patterns
Pattern Recognition Letters
Use of artificial neural networks for clinical diagnosis
Mathematics and Computers in Simulation - Special issue on neural networks/neural computing
Detection of seizure activity in EEG by an artificial neural network: a preliminary study
Computers and Biomedical Research
Neural Networks - Special issue on neural control and robotics: biology and technology
An unsupervised neural network systems for visual evoked potentials
Supervised and unsupervised pattern recognition
Autoassociative MLP in Sleep Spindle Detection
Journal of Medical Systems
Fuzzy and Neuro-Fuzzy Systems in Medicine
Fuzzy and Neuro-Fuzzy Systems in Medicine
Hidden Markov models for online classification of single trial EEG data
Pattern Recognition Letters
Symbolical Reasoning about Numerical Data: A Hybrid Approach
Applied Intelligence
A Tutorial on Support Vector Machines for Pattern Recognition
Data Mining and Knowledge Discovery
Using Hidden Markov Models to Build an Automatic, Continuous and Probabilistic Sleep Stager
IJCNN '00 Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 3 - Volume 3
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
High Accuracy Classification of EEG Signal
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
Automatic recognition of vigilance state by using a wavelet-based artificial neural network
Neural Computing and Applications
Artificial Neural Network Based Epileptic Detection Using Time-Domain and Frequency-Domain Features
Journal of Medical Systems
Neural network classification of late gamma band electroencephalogram features
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Pattern Recognition Letters
Neural Networks in Healthcare: Potential and Challenges
Neural Networks in Healthcare: Potential and Challenges
Genetic programming for epileptic pattern recognition in electroencephalographic signals
Applied Soft Computing
Computers in Biology and Medicine
Biometrics from Brain Electrical Activity: A Machine Learning Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
A study on fuzzy C-means clustering-based systems in automatic spike detection
Computers in Biology and Medicine
Neural Network-Based Diagnosing for Optic Nerve Disease from Visual-Evoked Potential
Journal of Medical Systems
An experimental evaluation of ensemble methods for EEG signal classification
Pattern Recognition Letters
Journal of Medical Systems
Genetic programming of conventional features to detect seizure precursors
Engineering Applications of Artificial Intelligence
Channel selection and feature projection for cognitive load estimation using ambulatory EEG
Computational Intelligence and Neuroscience - EEG/MEG Signal Processing
A Minimal Channel Set for Individual Identification with EEG Biometric Using Genetic Algorithm
ICCIMA '07 Proceedings of the International Conference on Computational Intelligence and Multimedia Applications (ICCIMA 2007) - Volume 02
EURASIP Journal on Advances in Signal Processing
The random electrode selection ensemble for EEG signal classification
Pattern Recognition
Journal of Medical Systems
Estimating VDT mental fatigue using multichannel linear descriptors and KPCA-HMM
EURASIP Journal on Advances in Signal Processing
Estimating the depth of anesthesia using fuzzy soft computation applied to EEG features
Intelligent Data Analysis
An efficient classifier to diagnose of schizophrenia based on the EEG signals
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Visual evoked potentials discrimination based on adaptive zero-tracking neural network
Computers in Biology and Medicine
Recurrent neural networks employing Lyapunov exponents for EEG signals classification
Expert Systems with Applications: An International Journal
Computerized recognition of Alzheimer disease-EEG using genetic algorithms and neural network
Future Generation Computer Systems
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A first attempt at constructing genetic programming expressions for EEG classification
ICANN'05 Proceedings of the 15th international conference on Artificial Neural Networks: biological Inspirations - Volume Part I
Multiclass Support Vector Machines for EEG-Signals Classification
IEEE Transactions on Information Technology in Biomedicine
Fuzzy detection of EEG alpha without amplitude thresholding
Artificial Intelligence in Medicine
Paper: Neural network based classification of single-trial EEG data
Artificial Intelligence in Medicine
Neuro-fuzzy closed-loop control of depth of anaesthesia
Artificial Intelligence in Medicine
Input-output HMMs for sequence processing
IEEE Transactions on Neural Networks
A local neural classifier for the recognition of EEG patterns associated to mental tasks
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
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Presently high density EEG systems are available at affordable cost, with which the data dimension has gone up considerably. For efficient computation of this high-dimensional data, various soft computing paradigms are receiving increasing attention. In this survey we have identified certain soft computing techniques (by soft computing techniques we mean computational techniques that take into account the inherent uncertainties in the data and/or in the computing model) for pattern recognition/data mining, such as, neural networks, fuzzy logic, evolutionary computation, statistical discrimination and Bayesian inference, which have turned out to be particularly useful in processing human scalp EEG. Wherever possible results of comparative studies among various techniques have been presented. Analyses of EEG for various feature extraction are exceedingly challenging pattern recognition tasks. This survey has shown that on an average the artificial neural networks and Bayesian approaches have emerged more successful in EEG analysis than the other soft computing paradigms. For readability the paper has been kept as little technical as possible. Large number of references have been listed to aid searching for the technical details.