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Title: Spiking neural network based approach to EEG signal analysis
Author: Goel, Piyush
ISNI:       0000 0004 2669 3984
Awarding Body: University of Portsmouth
Current Institution: University of Portsmouth
Date of Award: 2009
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The research described in this thesis presents a new classification technique for continuous electroencephalographic (EEG) recordings, based on a network of spiking neurons. Analysis of the signals is performed on ensemble EEG and the task of the neural network is to identify the P300 component in the signals. The network employs leaky-integrate-and-fire neurons as nodes in a multi-layered structure. The method involves formation of multiple weak classifiers to perform voting and collective results are used for final classification.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available