An Implicit Triplet Neural Network and Optical Fiber Nonlinear Damage Equalization Method
A nonlinear damage and neural network technology, applied in the field of implicit triplet neural network and optical fiber nonlinear damage equalization, can solve the problems of high complexity and more training data, and achieve the effect of low computational cost and less training data
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[0075] Two series of pseudo-random bit sequences (PRBS) are generated for each channel respectively for the transmission of two polarization states to attach figure 1 The mapping relationship of the two strings of PRBS is mapped to the constellation diagram to obtain dual-polarization 16QAM symbols, which are used as label symbol streams. According to the attached figure 2 Schematic diagram of the system to build a simulation system, and change the fiber input power and transmission distance (the fiber input power is from -4dBm to 2dBm per channel, the step is 1; the transmission distance is from 2400km to 4000km, the step is 80km), according to step 1 to generate different conditional dataset. The training set size ranges from 3000 symbols to 32768 symbols, and the validation and test sets are both 32768 symbols in size.
[0076] According to the attached image 3 The structure diagram of a constructs an implicit triplet neural network to be optimized. For datasets under...
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