摘要
文章提出基于人工智能的传感器网络微弱信号增强处理方法。建立传感器网络微弱信号增强指令协议,制定微弱信号识别、信号增强的指令格式,确保传感网络对微弱信号捕获、增强、传输的能力。利用深度学习、粒子群两种人工智能算法,将深度学习输出的信噪比作为微弱信号粒子的适应度评价函数,对微弱周期进行尺度变换,从而实现微弱信号增强。采用仿真实验,验证该方法的微弱信号增强处理效果更佳,能有效解决噪声干扰的问题。
This paper proposes a weak signal enhancement processing method based on artificial intelligence for sensor networks.It establishes an instruction protocol for enhancing weak signals within sensor networks and formulates the command formats for weak signal recognition and signal enhancement to ensure the network's capabilities in capturing,enhancing,and transmitting weak signals.By employing two artificial intelligence algorithms—deep learning and particle swarm optimization—the signal-to-noise ratio output by deep learning is utilized as the fitness evaluation function for weak signal particles,with scale transformations applied to weak periods to achieve signal enhancement.Simulation experiments demonstrate that this method offers superior performance in weak signal enhancement processing and effectively addresses issues caused by noise interference.
作者
安娜
An Na(Shaanxi Post and Telecommunication College,Xianyang 712000,China)
出处
《办公自动化》
2025年第8期84-86,共3页
Office Informatization
关键词
人工智能
传感器网络
微弱信号
信号增强
深度学习
artificial intelligence
sensor network
weak signal
signal enhancement
deep learning
