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Saeid Sanei
EEG Signal Processing and Machine Learning
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Страница 1
Table of Contents
List of Tables
List of Illustrations
Guide
Pages
Страница 7
Страница 8
Страница 9
Страница 10
Страница 11
List of Abbreviations
1 Introduction to Electroencephalography 1.1 Introduction
1.2 History
1.3 Neural Activities
1.4 Action Potentials
1.5 EEG Generation
1.6 The Brain as a Network
1.7 Summary
References
2 EEG Waveforms 2.1 Brain Rhythms
2.2 EEG Recording and Measurement
2.2.1 Conventional Electrode Positioning
2.2.2 Unconventional and Special Purpose EEG Recording Systems
2.2.3 Invasive Recording of Brain Potentials
2.2.4 Conditioning the Signals
2.3 Sleep
2.4 Mental Fatigue
2.5 Emotions
2.6 Neurodevelopmental Disorders
2.7 Abnormal EEG Patterns
2.8 Ageing
2.9 Mental Disorders 2.9.1 Dementia
2.9.2 Epileptic Seizure and Nonepileptic Attacks
2.9.3 Psychiatric Disorders
2.9.4 External Effects
2.10 Summary
References
3 EEG Signal Modelling 3.1 Introduction
3.2 Physiological Modelling of EEG Generation
3.2.1 Integrate‐and‐Fire Models
3.2.2 Phase‐Coupled Models
3.2.3 Hodgkin–Huxley Model
3.2.4 Morris–Lecar Model
3.3 Generating EEG Signals Based on Modelling the Neuronal Activities
3.4 Mathematical Models Derived Directly from the EEG Signals
3.4.1 Linear Models 3.4.1.1 Prediction Method
3.4.1.2 Prony's Method
3.4.2 Nonlinear Modelling
3.4.3 Gaussian Mixture Model
3.5 Electronic Models
3.5.1 Models Describing the Function of the Membrane
3.5.1.1 Lewis Membrane Model
3.5.1.2 Roy Membrane Model
3.5.2 Models Describing the Function of a Neuron 3.5.2.1 Lewis Neuron Model
3.5.2.2 The Harmon Neuron Model
3.5.3 A Model Describing the Propagation of the Action Pulse in an Axon
3.5.4 Integrated Circuit Realizations
3.6 Dynamic Modelling of Neuron Action Potential Threshold
3.7 Summary
References
4 Fundamentals of EEG Signal Processing 4.1 Introduction
4.2 Nonlinearity of the Medium
4.3 Nonstationarity
4.4 Signal Segmentation
4.5 Signal Transforms and Joint Time–Frequency Analysis
4.5.1 Wavelet Transform
4.5.1.1 Continuous Wavelet Transform
4.5.1.2 Examples of Continuous Wavelets
4.5.1.3 Discrete‐Time Wavelet Transform
4.5.1.4 Multiresolution Analysis
4.5.1.5 Wavelet Transform Using Fourier Transform
4.5.1.6 Reconstruction
4.5.2 Synchro‐Squeezed Wavelet Transform
4.5.3 Ambiguity Function and the Wigner–Ville Distribution
4.6 Empirical Mode Decomposition
4.7 Coherency, Multivariate Autoregressive Modelling, and Directed Transfer Function
4.8 Filtering and Denoising
4.9 Principal Component Analysis
4.9.1 Singular Value Decomposition
4.10 Summary
References
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