"EMR_Dataset_CSV"

"This dataset provides a structured collection of spectral\u2013temporal electromagnetic radiation (EMR) measurements designed for machine learning\u2013based signal classification and analysis. The dataset contains 15,000 samples distributed across five balanced classes, representing different electromagnetic signal sources or conditions. Each sample consists of 4,096 spectral\u2013temporal features, organized as measurements from 128 frequency channels observed over 32 time intervals, enabling detailed analysis of signal dynamics in both spectral and temporal domains. The dataset is intended for research in signal processing, electromagnetic environment monitoring, and artificial intelligence applications, including deep learning architectures such as CNN, RNN, and transformer-based models. It can support tasks such as source classification, anomaly detection, and intelligent spectrum monitoring, particularly in applications involving IoT sensing systems, UAV-based monitoring platforms, and wireless environment analysis."

本数据集提供了结构化的谱时域电磁辐射（Electromagnetic Radiation，EMR）测量集，专为基于机器学习的信号分类与分析任务设计。数据集共包含15000个样本，均匀分布于5个平衡类别中，分别对应不同的电磁信号源或信号状态。每个样本包含4096个谱时域特征，其结构为在32个时间间隔内对128个频率信道进行观测所得的测量数据，可实现信号在频谱域与时域的动态特性精细化分析。本数据集适用于信号处理、电磁环境监测及人工智能应用等领域的研究，可支持卷积神经网络（Convolutional Neural Network，CNN）、循环神经网络（Recurrent Neural Network，RNN）以及基于Transformer的模型等深度学习架构的相关研究。该数据集可支撑信号源分类、异常检测及智能频谱监测等任务，尤其适用于物联网（Internet of Things，IoT）感知系统、基于无人机（Unmanned Aerial Vehicle，UAV）的监测平台以及无线环境分析等应用场景。