Download e-book for kindle: Recent Advances in Brain-Computer Interface Systems by Reza Fazel

By Reza Fazel

ISBN-10: 9533071753

ISBN-13: 9789533071756

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Extra resources for Recent Advances in Brain-Computer Interface Systems

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In the second type of experiments the user receives the classification feedback from a simple classifier based on artificial neural networks. These neural networks have been trained with registers associated to each cognitive task obtained from the previous kind of experiments. Because in the first type of experiments there is not any kind of feedback they are named Off-line experimental procedures, in contrast to the second class called On-line experimental procedures. The flow of activities for each experimental procedure are described in the following subsections.

0-5 6-8 9 - 11 12 - 14 15 - 20 21 - 29 30 - 38 39 - 192 Denomination. Not considered θ. α1 . α2. β1 . β2 . β3 . Not considered Table 1. Feature vector. contrasts were applied to samples of both electroencephalographic channels preprocessed with each type of filtering window. • Bilateral contrast to the variance ratio. The equality of variances is obtained with R = 1. n1 : sample size of the first population. n2 : sample size of the second population. σ1 : variance of the first population. σ2 : variance of the second population.

Otherwise, the network is trained again. 6. Estimation of the network performance error. 7. Application of the neural net to the whole data set and result registration. 8. Calculation of the confusion matrices for each experiment. 1 Multi-Layer Perceptron Classifier The setup parameters used in this classifier are: Parameter Learning algorithm Number of output neurons Goal error Epochs Max. fail Mem. reduc. Min. grad. μ μ dec μ inc μ max Table 2. Parameters for MLP Classifiers. 2 Radial Basis Function Classifier The setup parameters used in this classifier are: • Number of hidden neurons: The learning algorithm used by this type of neural networks determines the number of neurons that are in the hidden layer through an iterative process (Horward Demuth, 2006).

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Recent Advances in Brain-Computer Interface Systems by Reza Fazel


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