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Epileptic seizure source identification involves neurologists combing through a substantial amount of data manually, which sometimes takes weeks per patient. This paper presents a methodology for minimizing the amount of data a neurologist has to analyze to identify the seizure focus. The method keeps the neurologist as the final decision maker and aids in the decision making process. It has to be...
The idea that a concept is properly learned by an agent when the agent is able to generate examples and non-examples of the concept, has motivated research on generative models. Generative models are trained with the aim of improving performance of tasks such as classification. In this paper, a Long Short Term Memory (LSTM) architecture for simultaneous generation-classification is presented. The...
General type-2 fuzzy logic systems (T2 FLS) constitute a powerful tool for coping with ubiquitous uncertainty in many engineering applications. However, the immense computational complexity associated with defuzzification of general T2 fuzzy sets still remains an unresolved issue and prohibits its practical use. This paper proposes a novel importance sampling based defuzzification method for general...
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