A New Method for Stranded Cable Crosstalk Estimation Based on BAS-BP Neural Network Algorithm Combined with FDTD Method
Keywords:
Back propagation (BP) neural network algorithm, Beetle antennae search (BAS) algorithm, Finite difference time domain (FDTD) method, Multiconductor transmission lines (MTL), Stranded cable crosstalkAbstract
In this paper, based on the research of back propagation (BP) neural network algorithm optimized by the beetle antennae search (BAS) algorithm, a new method for predicting stranded cable crosstalk is proposed. Firstly, the stranded wire model and the equivalent multiconductor transmission lines model are both established. Then, the extraction network of the stranded wire electromagnetic parameter matrix is constructed by using the BAS-BP neural network algorithm. Finally, the network is combined with the finite difference time domain (FDTD) method to solve the near end crosstalk (NEXT) and far end crosstalk (FEXT) of a specific three-core stranded model. The new method has good agreement with the crosstalk results obtained by the electromagnetic field numerical method. The validity of the new method is verified.
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