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System modeling and identification based on BP neu
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Based on BP neural network on with noise of second-order system of identification forecast, used typical of three layer network topology structure is entered layer, and implied layer and output layer, using minimum are party errors and gradient fell method, by errors of reverse spread to constantly adjustment system of right value threshold value, makes network output constantly to approximation actual system of output, simulation results indicates that BP network reached has expected identification of precision effect, implementation has nonlinear system of identification forecast.
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