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Discriminating psychogenic nonepileptic seizures (PNES) from epilepsy is challenging, and a reliable and automatic classification remains elusive. In this study, we develop an approach for discriminating between PNES and epilepsy using the common spatial pattern extracted from the brain network topology (SPN). The study reveals that 92% accuracy, 100% sensitivity, and 80% specificity were reached...
This paper uses the proposed two-stage kernel fisher discriminate analysis method to extract algebra feature of palmprint. It is to take each piece of palmprint image as a point of a high-dimensional space. The palmprint images from the training set form a training data set. Through a nonlinear mapping the input space of training data is mapped to a feature space, making different types of palm print...
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