Nonlinear impairment compensation using neural networks

Shinsuke Fujisawa, Fatih Yaman, Hussam G. Batshon, Massaki Tanio, Naoto Ishii, Chaoran Huang, Thomas Ferreira de Lima, Yoshihisa Inada, Paul R. Prucnal, Norifumi Kamiya, Ting Wang

Research output: Contribution to journalConference articlepeer-review


Neural networks are attractive for nonlinear impairment compensation applications in communication systems. In this paper, several approaches to reduce computational complexity of the neural network-based algorithms are presented.

Original languageEnglish (US)
JournalOptics InfoBase Conference Papers
StatePublished - 2021
EventOptical Fiber Communication Conference, OFC 2021 - Virtual, Online, United States
Duration: Jun 6 2021Jun 11 2021

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Mechanics of Materials


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