机器学习多频率微波识别数据

数据集是机器学习多频率微波识别数据，利用机器学习增强原子对于微波信号的识别能力，主要包括实验中微波信号在原子上产生透射谱的原始数据，以及使用机器学习识别信号的结果与分析数据。数据由光电探测器将光信号转换为电信号后，由示波器收集。This is a multi-frequency microwave recognition dataset for machine learning research, developed to improve the microwave signal recognition performance of atomic systems via machine learning methods. The dataset primarily includes two types of data: raw transmission spectrum data generated when microwave signals interact with atomic systems during experiments, as well as signal recognition results and corresponding analytical data obtained through machine learning-based signal recognition. All data is collected by an oscilloscope after photodetectors convert optical signals into electrical signals.

搜集汇总

背景与挑战

背景概述

该数据集聚焦于利用机器学习技术提升原子对多频率微波信号的识别能力。它包含了实验中微波信号在原子上产生的透射谱原始数据，以及通过机器学习进行信号识别的结果与分析数据，数据通过光电探测器和示波器采集。