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相关概念视频

Errors in Global Positioning System01:26

Errors in Global Positioning System

115
Global Positioning System (GPS) technology has revolutionized navigation and positioning, but its accuracy is often compromised by various errors. These errors, stemming from environmental, satellite, and receiver-related factors, require careful mitigation to ensure reliable performance across applications.Atmospheric ErrorsGPS signals travel through the Earth’s ionosphere and troposphere, introducing delays which affect accuracy. The ionosphere is strongly influenced by charged particles,...
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相关实验视频

Updated: Sep 16, 2025

Tracking Infiltration Front Depth Using Time-lapse Multi-offset Gathers Collected with Array Antenna Ground Penetrating Radar
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校正物理信息的神经网络辅助匹配场处理技术用于水下被动源范围估计.

Hongbo Miao1,2,3, Li Li1,2,3,4, Yuxiang Zhang1,2,3

  • 1National Key Laboratory of Underwater Acoustic Technology, Harbin Engineering University, Harbin 150001, China.

The Journal of the Acoustical Society of America
|July 9, 2025
PubMed
概括
此摘要是机器生成的。

一种新的方法,纠正物理信息的神经网络辅助匹配场处理 (CrPIMFP),通过使用最小的数据纠正环境不匹配,改善了水下被动源范围. 这种强大的技术在具有挑战性的浅水条件下提高了准确性.

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Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example
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科学领域:

  • 声学 声学 在声学方面
  • 机器学习 机器学习
  • 信号处理 信号处理

背景情况:

  • 匹配的现场处理 (MFP) 对于水下被动源范围至关重要.
  • 环境不匹配,特别是复制生成,对MFP准确性构成重大挑战.

研究的目的:

  • 提出一个数据高效和符合物理学的测距方法,纠正物理信息的神经网络辅助MFP (CrPIMFP).
  • 为了减轻水下被动源范围中的复制环境不匹配.

主要方法:

  • 开发了一个校正物理信息的神经网络 (CrPINN) 以使用最小的测量数据来校正声学传播模型复制品.
  • 整合正常化校正损失,赫尔姆霍尔茨方程和边界条件到CrPINN损失函数中.
  • 启用对未采样点的复制插值,减少对标记数据的依赖.

主要成果:

  • 与传统的MFP相比,CrPIMFP对底层沉积物深度/声速不匹配以及范围依赖的环境的抵抗性增加.
  • 在SWellEx-96环境中的实验结果证实了CRPIMFP在各种场景中的卓越性能,包括有限的训练数据,概括,稀疏数组和长距离.

结论:

  • CrPIMFP显著减少了纠正的复制品和测量的领域之间的差异,提高了MFP的距离性能.
  • 拟议的方法表现出强度和优于传统的距离算法,验证了其在各种水下声学条件中的有效性.