Evolving Probabilistic Spiking Neural Networks: Modelling and Pattern Recognition of  Spatio-temporal Brain Data (Eeg) - Nuttapod Nuntalid - Books - LAP LAMBERT Academic Publishing - 9783659430800 - July 17, 2013
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Evolving Probabilistic Spiking Neural Networks: Modelling and Pattern Recognition of Spatio-temporal Brain Data (Eeg)

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The use of Electroencephalography (EEG) in Brain Computer Interface (BCI) domain presents a challenging problem due to presence of spatial and temporal aspects inherent in the EEG data. Many studies either transform the data into a temporal or spatial problem for analysis. This approach results in loss of significant information since these methods fail to consider the correlation present within the spatial and temporal aspect of the EEG data. However, Spiking Neural Network (SNN) naturally takes into consideration the correlation present within the spatio-temporal data. Hence by applying the proposed SNN based novel methods on EEG, the thesis provide improved analytic on EEG data. This book introduces novel methods and architectures for spatio-temporal data modelling and classification using SNN. More specifically, SNN is used for analysis and classification of spatiotemporal EEG data.

Media Books     Paperback Book   (Book with soft cover and glued back)
Released July 17, 2013
ISBN13 9783659430800
Publishers LAP LAMBERT Academic Publishing
Pages 256
Dimensions 150 × 15 × 225 mm   ·   381 g
Language English