Deep learning as a highly efficient tool for digital signal processing design

Andrey Pryamikov

doi:10.1038/s41377-024-01599-8

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Deep learning as a highly efficient tool for digital signal processing design

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- Deep learning as a highly efficient tool for digital signal processing design
- Deep learning as a highly efficient tool for digital signal processing design
- LSA 2024年13卷第11期页码：2434-2435
- Affiliations：
  
  Prokhorov General Physics Institute of the Russian Academy of Sciences, Moscow, Russia
- Author bio：
  
  Andrey Pryamikov (pryamikov@mail.ru)
- Funds：
- DOI：10.1038/s41377-024-01599-8
  中图分类号：
- 网络出版日期：2024-09-11，
  
  纸质出版日期：2024-11-30
- Accepted：
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Deep learning as a highly efficient tool for digital signal processing design[J]. LSA, 2024,13(11):2434-2435.

Pryamikov, A. Deep learning as a highly efficient tool for digital signal processing design. Light: Science & Applications, 13, 2434-2435 (2024).
Deep learning as a highly efficient tool for digital signal processing design[J]. LSA, 2024,13(11):2434-2435. DOI： 10.1038/s41377-024-01599-8.

Pryamikov, A. Deep learning as a highly efficient tool for digital signal processing design. Light: Science & Applications, 13, 2434-2435 (2024). DOI： 10.1038/s41377-024-01599-8.

摘要

Abstract

The backpropagation algorithm

the most widely used algorithm for training artificial neural networks

can be effectively applied to the development of digital signal processing schemes in the optical fiber transmission systems. Digital signal processing as a deep learning framework can lead to a new highly efficient paradigm for cost-effective digital signal processing designes with low complexity.

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references

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