Efficient Framework for Extracting Desired EEG Signals using Robust Filtering Mechanism
Syed Mohammad Ali · International Journal for Research in Applied Science and Engineering Technology · 2017
A robust architecture based on quantum mechanics is proposed for processing neural information with the help of Schrodinger Wave Equation (SWE). Non-stationary stochastic signal is represented as a time varying wave packets that is characterized by Recurrent quantum neural network (RQNN).Statistical behavior of the input signal is effectively captured and signal embedded noise is estimated by RQNN algorithm. In order to increase the signal separability, Motor Imagery (MI) based Brain Computer Interface (BCI) is used to filter the Electroencephalogram (EEG) signals before feature extraction and classification. Brain Computer Interface performance is improved by RQNN EEG filtering.