arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2005.08785eess.SPcs.ITcs.LGmath.IT
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基于端到端深度学习的光纤通信系统

Optical Fiber Communication Systems Based on End-to-End Deep Learning

University College London(伦敦大学学院);Karlsruhe Institute of Technology(卡尔斯鲁厄理工学院);Nokia Bell Labs(诺基亚贝尔实验室)

Boris Karanov, Mathieu Chagnon, Vahid Aref, Domanic Lavery, Polina Bayvel, Laurent Schmalen

摘要:

我们研究基于前馈或双向循环神经网络(BRNN)和深度学习的端到端优化光传输系统。特别是,我们报告的第一个实验演示的BRNN自动编码器,突出的性能改善与经常性处理的通信分散的非线性信道。

英文摘要:

We investigate end-to-end optimized optical transmission systems based on feedforward or bidirectional recurrent neural networks (BRNN) and deep learning. In particular, we report the first experimental demonstration of a BRNN auto-encoder, highlighting the performance improvement achieved with recurrent processing for communication over dispersive nonlinear channels.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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