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Titlebook: Advances in Neural Networks – ISNN 2012; 9th International Sy Jun Wang,Gary G. Yen,Marios M. Polycarpou Conference proceedings 2012 Springe

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https://doi.org/10.1007/978-3-642-31362-2algorithms; extreme learning machines; feature selection; fuzzy neural networks; machine learning; algori
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Kevin Gournay,Grant Devilly,Charles Brookerod and discuss its comprehensive design methodology. As the pre-processing part, LDA algorithm is combined in front of input layer and then the new feature samples obtained through LDA are to be the input data of FRBF neural networks. In the hidden layer, FCM algorithm is used as receptive field ins
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Kevin Gournay,Grant Devilly,Charles Brooker local energy histogram method has been proposed to alleviate the difficulty in modeling wavelet subband coefficients with a previously assumed distribution function. Actually, the similarity between any two local energy histograms was measured by a symmetrized Kullback-Leibler divergence (SKLD). Ho
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Community Quality-of-Life Indicatorsd neural network is proposed. In the proposed algorithm, Morlet complex wavelet is used to obtain the WT-based SK of two kinds of disturbances, such as the impulse transient and oscillation transient. Two characteristic quantities, i.e., the maximum value of SK and the frequencies of the signals, ar
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https://doi.org/10.1007/978-3-030-48182-7ed on approximate Markov blanket. The relevant features are selected according to the mutual information between the features and the output. To identify the redundant features, a heuristic method is proposed to approximate Markov blanket. A redundant feature is identified according to whether there
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