Yishi SUN, Yi SUN. Parameter prediction of classical- quantum signals co- fiber transmission system based on BP neural network[J]. Chinese Journal of Quantum Electronics, 2023, 40(4): 546

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- Chinese Journal of Quantum Electronics
- Vol. 40, Issue 4, 546 (2023)

Fig. 1. Structure diagram of WDM-QKD system

Fig. 2. Comparison of the detection rates of SRS noise, FWM noise and out-band noise

Fig. 3. The secure key transmission relationship under different decoy state methods with statistical fluctuations

Fig. 4. Training performance of neural network with different distribution of neurons. (a) Neuron setup (3, 2, 1); (b) Neuron setup (6, 4, 1); (c) Neuron setup (15, 10, 1); (d) Neuron setup (48, 24, 1)

Fig. 5. Training performance of neural network with LM variable gradient algorithm

Fig. 6. Training performance of neural network with Bayesian regularization algorithm

Fig. 7. Training performance of neural network with SCG algorithm

Fig. 8. BP neural network model

Fig. 9. Light source prediction results using BP neural network. (a) Imitative effect; (b) Training error
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Table 1. Propagation algorithm of BP neural network
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Table 2. Parameters used for the numerical simulation of WDM-QKD

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