面向新一代通信需求的光纤卷积神经网络研究数据

该数据来源于基于时域拉伸技术的光纤卷积神经网络。该成果利用光纤通信器件中的调制器、激光器、光纤等构建神经网络系统进行智能模式识别。该数据由Matlab和Optisystem生成。该成果经由同行评议，已发表于Science China Information Sciences上。支撑论文“Optoelectronic convolutional neural networks based on time-stretch method”该结构可应对下一代高速大容量光纤通信系统中的智能识别需求。This dataset is derived from an optoelectronic convolutional neural network based on the time-stretch technique. This work constructs a neural network system for intelligent pattern recognition by utilizing components in optical fiber communication systems, including modulators, lasers, and optical fibers. This dataset was generated using Matlab and OptiSystem. This work has undergone peer review and been published in *Science China Information Sciences*, supported by the paper entitled "Optoelectronic Convolutional Neural Networks Based on Time-Stretch Method". This structure can address the intelligent recognition demands in next-generation high-speed and high-capacity optical fiber communication systems.

搜集汇总

背景与挑战

背景概述

该数据集包含基于时域拉伸技术的光纤卷积神经网络研究数据，由Matlab和Optisystem生成，相关成果已发表于Science China Information Sciences。该数据旨在支持下一代高速大容量光纤通信系统中的智能模式识别需求。