To solve the problems of high complexity and low accuracy in Volterra time-domain kernel calculation of a nonlinear system, this\npaper proposes an intelligent calculation method of Volterra time-domain kernel by time-delay artificial neural networks\n(TDANNs) and also designs a root mean square error (RMSE) index to choose the neuron number of the network input layer.\nFirstly, a three-layer TDANN is designed according to the characteristics of the Volterra model. Secondly, the relationship\nbetween parameters of TDANN and Volterra time-domain kernel is analyzed, and then three-order expressions of Volterra timedomain\nkernel are derived. The calculation of Volterra time-domain kernel is completed by network training. Finally, it is verified\nby a nonlinear system. Simulation results indicate that compared with traditional methods, the new method has higher accuracy,\nand it can realize the batch calculation of Volterra kernel, which not only improves the calculation efficiency but also provides\naccurate data for fault diagnosis based on Volterra kernel in further research work.
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