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Updated: May 31, 2025

Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform
06:25

Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform

Published on: February 12, 2014

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一种视线/非视线识别方法,基于全面特征的动态多层次优化

Ziyao Ma1, Zhongliang Deng1, Zidu Tian1

  • 1School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China.

Sensors (Basel, Switzerland)
|January 25, 2025
PubMed
概括

本研究引入了一种新的深度学习模型,用于准确识别视线 (LOS) 和非视线 (NLOS) 5G信号传播. 这通过提高信号测量精度,提高了复杂环境中的高精度定位.

关键词:
5G CIR 的使用情况认可LOS/NLOS的认可层次结构的特征是层次的特征.马巴马巴马巴 马巴马巴 马巴巴时间延迟神经网络神经网络

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