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In this paper, we present the application of radial basis function (RBF) neural network for aerodynamic parameter estimation. The Two-Stage RBF neural network (NN) architecture is proposed for complete aerodynamic modelling. The RBF NN is trained by hybrid learning using K-means clustering and recursive least squares (RLS) methods. The proposed architecture yields the significant improvements for...
Motor imagery (MI) based electroencephalogram (EEG) signals are a widely used form of input in brain computer interface systems (BCIs). Although there are a number of ways to classify data, a question still persists as to which technique should be employed in the domain of MI based EEG signals. In this paper, an attempt is made to find the best classification algorithm and feature extraction technique...
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