大数据技术在电子信息工程中的创新应用

Innovative Application of Big Data Technology in Electronic Information Engineering

摘要:

文中围绕大数据技术在电子信息工程中的创新应用展开研究,提出了高速信号采集与实时预处理、异构数据源融合及特征工程优化的方法,结合深度学习、强化学习与图神经网络,实现了信号识别、通信优化与故障诊断,同时设计了分布式计算与边缘计算混合架构,优化了实时性、可靠性与能效。实验结果表明,在10 Gbps采样率下信号恢复精度达98%,频谱利用率提升30%,故障定位准确率提高至95%,处理延迟降低40%。研究为电子信息系统智能化与高效化提供了可行方案。

Abstract:

This paper researches the innovative application of big data technology in electronic information engineering. It proposes methods for high-speed signal acquisition and real-time preprocessing, heterogeneous data source fusion, and feature engineering optimization. Combined with deep learning, reinforcement learning and graph neural networks, signal recognition, communication optimization and fault diagnosis are realized. Meanwhile, a hybrid architecture integrating distributed computing and edge computing is designed to optimize real-time performance, reliability and energy efficiency. The experimental results show that at a 10 Gbps sampling rate, the signal recovery accuracy reaches 98%, the spectrum utilization rate is increased by 30%, the fault location accuracy is increased to 95%, and the processing delay is reduced by 40%. The research provides a feasible solution for the intelligence and efficiency of electronic information systems.