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The traditional BP learning algorithm converges slowly, and obviously depends on the step size. The paper has proposed a step-size rule using to improve BP algorithm. In the network training, it can search a relatively reasonable step length in each iteration, so it can reduce the impact of the choice of step length on learning speed greatly. The simulation(More)
In this paper, a nonlinear model based on RBF Neural Network is presented. There are some ameliorated measures in leaning algorithm of Radial Basis Function (RBF) neural network. The number and the centric value of hidden layer are determined by using immune algorithm. The supervisory algorithm is taken as method of adjustable weight of output layer. Using(More)
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