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In this paper the robustness of three different types of Fuzzy Flip-Flop based Neural Network (FNN) and the standard tansig based neural networks is compared from the various test function approximation goodness points of view. It is tested how well the fuzzy flip-flop based and the simulated neural networks handle the test data sets outlier points. The robust design of the FNN is presented, and the...
In this paper, a hybrid speed controller based on proportional integral (PI) controller and artificial neural network(ANN) is proposed as a speed controller for an indirect field oriented induction motor vector control system. The new controller has self-learning and self-organization capabilities. Its parameters are adjusted online according to back propagation (BP) algorithm. The weighting coefficients...
Recently Extreme Learning Machine (ELM) has been attracting attentions for its simple and fast training algorithm, which randomly selects input weights. Given sufficient hidden neurons, ELM has a comparable performance for a wide range of regression and classification problems. However, in this paper we argue that random input weight selection may lead to an ill-conditioned problem, for which solutions...
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