A neural network for forward and inverse nonlinear Fourier transforms for fiber optic communication
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arXiv
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866917722798948352 |
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| author | Zhang, Wen Qi Chan, Terence H. V., Shahraam Afshar |
| author_facet | Zhang, Wen Qi Chan, Terence H. V., Shahraam Afshar |
| contents | We propose a neural network for both forward and inverse continuous nonlinear Fourier transforms, NFT and INFT respectively. We demonstrate the network's capability to perform NFT and INFT for a random mix of NFDM-QAM signals. The network transformations (NFT and INFT) exhibit true characteristics of these transformations; they are significantly different for low and high-power input pulses. The network shows adequate accuracy with an RMSE of 5e-3 for forward and 3e-2 for inverse transforms. We further show that the trained network can be used to perform general nonlinear Fourier transforms on arbitrary pulses beyond the training pulse types. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2407_11093 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | A neural network for forward and inverse nonlinear Fourier transforms for fiber optic communication Zhang, Wen Qi Chan, Terence H. V., Shahraam Afshar Signal Processing Optics We propose a neural network for both forward and inverse continuous nonlinear Fourier transforms, NFT and INFT respectively. We demonstrate the network's capability to perform NFT and INFT for a random mix of NFDM-QAM signals. The network transformations (NFT and INFT) exhibit true characteristics of these transformations; they are significantly different for low and high-power input pulses. The network shows adequate accuracy with an RMSE of 5e-3 for forward and 3e-2 for inverse transforms. We further show that the trained network can be used to perform general nonlinear Fourier transforms on arbitrary pulses beyond the training pulse types. |
| title | A neural network for forward and inverse nonlinear Fourier transforms for fiber optic communication |
| topic | Signal Processing Optics |
| url | https://arxiv.org/abs/2407.11093 |