公开(公告)号：US20250131283A1

公开(公告)日：2025-04-24

申请号：US18901798

申请日：2024-09-30

Applicant: NEC Laboratories America, Inc.

Inventor： Yue-Kai Huang ,  Zehao Wang

IPC: G06N3/096 ,  G06N3/067

Abstract: Disclosed are systems and methods directed to transfer learning of cascaded EDFA models error accumulations in a multi-span system in which a two-step method using transfer learning is employed to reduce EDFA model error accumulation in a multi-span system. A first step of employs existing pretrained component-level ML-based EDFA models in chain to create a large synthetic dataset. The synthetic dataset includes all related features and labels for a specific end-to-end link. A source model is trained based on the large synthetic dataset. To accommodate a performance prediction gap between real link condition and the source model, which is trained on synthetic dataset, our method employs a second step that collects a few measurements from the real end-to-end link and makes few-shots learning to transfer the synthesis-data-based source model to real-data-based target model.