mlsanityData to 13 Oct 2026

Fiber neural networks for the intelligent optical fiber communications

arXiv 2408.12602 ↗First posted 7 Aug 2024eess.SP cs.AI cs.NIcited by 0

Not on the map. Why?

Abstract (arXiv)

Optical neural networks have long cast attention nowadays. Like other optical structured neural networks, fiber neural networks which utilize the mechanism of light transmission to compute can take great advantages in both computing efficiency and power cost. Though the potential ability of optical fiber was demonstrated via the establishing of fiber neural networks, it will be of great significance of combining both fiber transmission and computing functions so as to cater the needs of future beyond 5G intelligent communication signal processing. Thus, in this letter, the fiber neural networks and their related optical signal processing methods will be both developed. In this way, information derived from the transmitted signals can be directly processed in the optical domain rather than being converted to the electronic domain. As a result, both prominent gains in processing efficiency and power cost can be further obtained. The fidelity of the whole structure and related methods is demonstrated by the task of modulation format recognition which plays important role in fiber optical communications without losing the generality.

Key facts. No citing papers in the map yet (data through 13 Oct 2026). Builds on 6 of its 20 references that are in the map. First posted on arXiv 7 Aug 2024.

Builds on

6 of 20 references.

References · 6

  1. 2018All-Optical Machine Learning Using Diffractive Deep Neural Networkscited by 177
  2. 2018End-to-end Deep Learning of Optical Fiber Communicationscited by 18
  3. 2020Fast and Accurate Optical Fiber Channel Modeling Using Generative Adversarial Networkcited by 6
  4. 2021Principle-driven Fiber Transmission Model based on PINN Neural Networkcited by 3
  5. 2021Machine-learning custom-made basis functions for partial differential equationscited by 3
  6. 2019Electro-optical Neural Networks based on Time-stretch Methodcited by 1

Built on by

Not cited yet.