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LAP Lambert Academic Publishing Evolving Probabilistic Spiking Neural Networks: Modelling and Pattern Recognition of Spatio-temporal Brain Data (EEG)

Name: Evolving Probabilistic Spiking Neural Networks: Modelling and Pattern Recognition of Spatio-temporal Brain Data (EEG)
Brand: LAP Lambert Academic Publishing

AI & Machine Learning

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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.

Product Specifications

Brand: LAP Lambert Academic Publishing
Format: paperback
ASIN: 3659430803
Category: Books > Subjects > Computing & Internet > Computer Science > AI & Machine Learning
Domain: Amazon UK
Release Date: 17 July 2013
Listed Since: 23 July 2013

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LAP Lambert Academic Publishing Evolving Probabilistic Spiking Neural Networks: Modelling and Pattern Recognition of Spatio-temporal Brain Data (EEG)

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