深度学习是数字信号处理设计的高效工具

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Light-Science & Applications Pub Date : 2024-09-11 DOI:10.1038/s41377-024-01599-8

Andrey Pryamikov

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引用次数: 0

摘要

反向传播算法是人工神经网络训练中应用最广泛的算法，可有效地应用于光纤传输系统中数字信号处理方案的开发。数字信号处理作为一种深度学习框架，可以为低复杂度、高性价比的数字信号处理设计带来一种新的高效范式。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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

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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来源期刊

Light-Science & Applications 数理科学, 物理学I, 光学, 凝聚态物性 II ：电子结构、电学、磁学和光学性质, 无机非金属材料, 无机非金属类光电信息与功能材料, 工程与材料, 信息科学, 光学和光电子学, 光学和光电子材料, 非线性光学与量子光学

自引率

0.00%

发文量

803

审稿时长

2.1 months