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RBF neural network based on \(q\)-Gaussian function in function approximation. (English) Zbl 1267.68200
Summary: To enhance the generalization performance of radial basis function (RBF) neural networks, an RBF neural network based on a \(q\)-Gaussian function is proposed. A \(q\)-Gaussian function is chosen as the radial basis function of the RBF neural network, and a particle swarm optimization algorithm is employed to select the parameters of the network. The non-extensive entropic index \(q\) is encoded in the particle and adjusted adaptively in the evolutionary process of population. Simulation results of the function approximation indicate that an RBF neural network based on \(q\)-Gaussian function achieves the best generalization performance.
68T05 Learning and adaptive systems in artificial intelligence
92B20 Neural networks for/in biological studies, artificial life and related topics
Full Text: DOI
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