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- W2359456827 abstract "Aimed at the shortage of gradient descent(GD) method which causes the slow speed of convergence and the problem of local minimization on the RBF neural network,a neural network with transcendental knowledge is proposed to control the learning rate in gradient descent method.Two RBF neural networks are built in this method.One neural network with transcendental knowledge is named a network and the other is named B network.When the problem of local minimization on B network comes up,an optimization learning rate is provided by A network to improve the speed of convergence of B network.Experimental results demonstrate the effectiveness and the advantage of this method.And it also can solve the similar problems very well." @default.
- W2359456827 created "2016-06-24" @default.
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- W2359456827 date "2009-01-01" @default.
- W2359456827 modified "2023-09-26" @default.
- W2359456827 title "Improved learning algorithm of RBF network and its application in similarity" @default.
- W2359456827 hasPublicationYear "2009" @default.
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