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In this paper, a new approach for function approximation problem is proposed to obtain better generalization performance and faster convergent rate. It is well known that gradient-based learning algorithm for feedforward neural networks (FNN) such as backpropagation (BP) algorithm is apt to be trapped in local minima, which leads to worse generalization performance and slower convergence rate. Therefore,...
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