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Erschienen in:
Classifying Human Activities with Temporal Extension of Random Forest Kapitel lesen Erstes Kapitel lesen

2016 | OriginalPaper | Buchkapitel

A Review of EEG Signal Simulation Methods

verfasst von : Muhammad Izhan Noorzi, Ibrahima Faye

Erschienen in: Neural Information Processing

Verlag: Springer International Publishing

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Abstract

This paper describes EEG signal simulation methods. Three main methods have been included in this study: Markov Process Amplitude (MPA), Artificial Neural Network (ANN), and Autoregressive (AR) models. Each method is described procedurally, along with mathematical expressions. By the end of the description of each method, the limitations and benefits are described in comparison with other methods. MPA comprises of three variations; first-order MPA, nonlinear MPA, and adaptive MPA. ANN consists of two variations; feed forward back-propagation NN and multilayer feed forward with error back-propagation NN with embedded driving signal. AR model based filtering has been considered with its variation, genetic algorithm based on autoregressive moving average (ARMA) filtering.

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Vorheriges Kapitel Performance Improvement via Bagging in Ensemble Prediction of Chaotic Time Series Using Similarity of Attractors and LOOCV Predictable Horizon
Nächstes Kapitel A New Blind Image Quality Assessment Based on Pairwise
Fußnoten
1
signum function or sgn (x)
$$ sgn(x) = {\left\{ \begin{array}{ll} 1 &{} \quad \text {if } x \ge 0\\ -1 &{} \quad \text {if } x < 0\\ \end{array}\right. }. $$
 
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Metadaten
Titel
A Review of EEG Signal Simulation Methods
verfasst von
Muhammad Izhan Noorzi
Ibrahima Faye
Copyright-Jahr
2016
Buch
Neural Information Processing

Print ISBN: 978-3-319-46680-4

Electronic ISBN: 978-3-319-46681-1

Copyright-Jahr: 2016

DOI
https://doi.org/10.1007/978-3-319-46681-1_71

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