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相关概念视频

Echo01:06

Echo

470
The human ear cannot distinguish between two sources of sound if they happen to reach within a specific time interval, typically 0.1 seconds apart. More than this, and they are perceived as separate sources.
Imagine the sound is reflected back to the ears. Assuming that the source is very close to the human, the difference between hearing the two sounds—the emitted sound and the reflected sound—may be more than the minimum time for perceiving distinct sounds. If this is the case,...
470

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基于扩散的声音源定位使用分布式网络的麦克风阵列.

Davide Albertini1, Alberto Bernardini1, Gioele Greco1

  • 1Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133 Milan, Italy.

Sensors (Basel, Switzerland)
|April 12, 2025
PubMed
概括
此摘要是机器生成的。

本研究介绍了使用麦克风阵列进行3D声音源本地化 (SSL) 的分布式优化方法. 拟议的方法提高了准确性和稳定性,即使在连接稀疏的网络中,通过自适应地惩罚表现不佳的数组.

关键词:
空中交通管制的扩散.处理麦克风阵列处理的麦克风阵列.声音源的本地化 声音源的本地化无线声学传感器网络无线声学传感器网络

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科学领域:

  • 声学和信号处理
  • 分布式系统 分布式系统
  • 优化理论 优化理论

背景情况:

  • 传统的3D声音源本地化 (SSL) 的麦克风阵列网络通常依赖于集中式数据处理,这给可扩展性和稳定性带来了挑战.
  • 现有的方法可能会在网络连接和不同的声学条件 (如反响和信号噪声比 (SNR)) 中扎.

研究的目的:

  • 重构3D声音源本地化 (SSL) 作为一个分布式优化问题,以提高网络性能.
  • 为麦克风阵列网络引入和评估计算分布式的适应然后组合 (ATC) 策略.
  • 开发适应性合作策略,通过惩罚表现不佳的数组来提高本地化准确性.

主要方法:

  • 作为一个分布式优化问题,用麦克风阵列网络重新构建3D SSL.
  • 实施一个计算分布式的适应-然后-组合 (ATC) 扩散策略.
  • 开发适应性合作策略,使用基于错误和基于距离的对阵列性能处罚.
  • 在模拟的声学环境中评估性能,声波和SNR水平各不相同.

主要成果:

  • 拟议的分布式ATC方法实现了高定位精度和稳定性.
  • 适应性合作策略有效地惩罚有害的阵列贡献,提高整体性能.
  • 该方法即使在连接稀疏的网络中也表现出稳定性.

结论:

  • 分布式优化框架为3D声音源本地化提供了可扩展和强大的解决方案.
  • 适应性合作策略对于优化分散式麦克风阵列系统的性能至关重要.
  • 这种方法在各种声条件和网络拓中保持了准确性和稳定性.