基于 ML 的多解码器注意力框架用于多跳光功率谱演化建模
机器学习
2025-03-24 v1 网络与互联网体系结构
摘要
我们实现了一个基于机器学习的注意力框架，采用组件特定的解码器，提高了在多跳网络中的光功率谱预测精度。通过减少对每个组件深入训练的需求，该框架可以扩展到具有最小数据收集的多跳拓扑结构，适用于棕场场景。
关键词
引用
@article{arxiv.2503.17072,
title = {Multi-Span Optical Power Spectrum Evolution Modeling using ML-based Multi-Decoder Attention Framework},
author = {Agastya Raj and Zehao Wang and Frank Slyne and Tingjun Chen and Dan Kilper and Marco Ruffini},
journal= {arXiv preprint arXiv:2503.17072},
year = {2025}
}
备注
This paper is a preprint of a paper accepted in ECOC 2024 and is subject to Institution of Engineering and Technology Copyright. A copy of record will be available at IET Digital Library