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Updated: May 22, 2025

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基于LSTM-DNN混合模型的紫外线通信中的通道均等化

Liwei Zhang1

  • 1School of Computer Information Engineering, Nanchang Institute of Technology, Nanchang, China. zlw810305@163.com.

Scientific reports
|May 18, 2025
PubMed
概括

这项研究引入了一个长短期记忆 - 深度神经网络 (LSTM-DNN) 模型,通过降低因信号减弱引起的比特误差率 (BER) 和平均平方误差 (MSE) 来改善紫外线通信 (UVC).

关键词:
比特错误率比特错误率是多少一个LSTM-DNN混合神经网络.平均平方误差 平均平方误差信号减弱 信号减弱 信号减弱紫外线通信中的紫外线.

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