Abstract
Based on the research of Monte Carlo (MC) method and adaptive beetle antennae search (ABAS) algorithm, a new crosstalk estimation method for non-uniform pitch twisted pair is proposed in this paper. First, the model of non-uniform pitch twisted pair is established based on the principle of twisted pair production. Then, the MC method and ABAS-BPNN (back propagation neural network) algorithm are used to construct a parasitic parameter mean extraction network for non-uniform pitch twisted pairs. Finally, the network is combined with the finite difference time domain (FDTD) algorithm to predict crosstalk. In the verification and analysis part of the numerical experiments, on the one hand, the ABAS-BPNN algorithm model is compared with the basic BAS-BPNN algorithm model, the BPNN algorithm model and the GA (genetic algorithm) -BPNN algorithm model, verifying the accuracy and efficiency of the improved BAS-BPNN algorithm. On the other hand, the validity and applicability of the proposed method in crosstalk prediction for non-uniform pitch twisted pair are verified by comparison with the results of the transmission line matrix (TLM) algorithm.
Highlights
Among various cables, twisted-pair cables are used in special fields such as robots and aviation because of their superior anti-interference performance [1]
Based on the Monte Carlo (MC) idea combined with the adaptive beetle antennae search (ABAS)-BP neural network algorithm, this paper proposes a method for estimating crosstalk of non-uniform pitch twisted-pair wires
The non-uniform pitch twisted pair RLCG parameter matrix extraction method based on the MC method, the ABASBP neural network and the finite difference time domain (FDTD) algorithm are used to calculate its crosstalk, which is called the new method here
Summary
Among various cables, twisted-pair cables are used in special fields such as robots and aviation because of their superior anti-interference performance [1]. By analyzing the manufacturing process of twisted pair, this paper defines the manufacturing parameters of twisted pair as a random variable that obeys the normal distribution, and establishes a mathematical model of non-uniform pitch twisted pair. This paper uses the FDTD algorithm combined with the above-mentioned p.u.l. parasitic parameter mean matrix of non-uniform pitch twisted-pair to predict the near end crosstalk () and far end crosstalk (FEXT) of a specific non-uniform pitch twisted-pair wire, conducts crosstalk analysis. Based on the MC idea combined with the ABAS-BP neural network algorithm, this paper proposes a method for estimating crosstalk of non-uniform pitch twisted-pair wires.
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