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相关概念视频

Linear Approximation in Frequency Domain01:26

Linear Approximation in Frequency Domain

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Linear systems are characterized by two main properties: superposition and homogeneity. Superposition allows the response to multiple inputs to be the sum of the responses to each individual input. Homogeneity ensures that scaling an input by a scalar results in the response being scaled by the same scalar.
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear....
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Perceiving Loudness, Pitch, and Location01:21

Perceiving Loudness, Pitch, and Location

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The human brain perceives pitch through two primary mechanisms reflected in place theory and frequency theory. Each mechanism describes how sound waves are interpreted as specific pitches by the brain, offering insights into the intricate processes of auditory perception.
Place theory, or place coding, suggests that different pitches are heard because various sound waves activate specific locations along the cochlea's basilar membrane. The brain determines the pitch of a sound by...
276
Sinusoidal Sources01:18

Sinusoidal Sources

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Direct current (DC) refers to an electric current that flows in a single direction, maintaining a constant polarity. This is in contrast to alternating current (AC), which periodically changes its direction and magnitude. AC forms the backbone of modern electricity transmission and distribution systems due to its efficient long-distance transmission capabilities.
In homes, the power supplies use sinusoidal sources to provide electricity. These sources generate a voltage that varies sinusoidally...
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Standing Electromagnetic Waves01:15

Standing Electromagnetic Waves

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Electromagnetic waves can be reflected; the surface of a conductor or a dielectric can act as a reflector. As electric and magnetic fields obey the superposition principle, so do electromagnetic waves. The superposition of an incident wave and a reflected electromagnetic wave produces a standing wave analogous to the standing waves created on a stretched string.
Suppose a sheet of a perfect conductor is placed in the yz-plane, and a linearly polarized electromagnetic wave traveling in the...
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Standing Waves in a Cavity01:28

Standing Waves in a Cavity

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A household microwave and lasers are examples of standing electromagnetic waves in a cavity. When two conducting metal plates are placed parallel at the nodal planes, it creates a cavity where standing waves are formed. The cavity between the two planes is analogous to a stretched string held at the points x = 0 and x = L. Here, the distance 'L' between the two planes must be an integer multiple of half of the wavelength. The wavelengths that satisfy this condition are given by:
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Linear Approximation in Time Domain01:21

Linear Approximation in Time Domain

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Nonlinear systems often require sophisticated approaches for accurate modeling and analysis, with state-space representation being particularly effective. This method is especially useful for systems where variables and parameters vary with time or operating conditions, such as in a simple pendulum or a translational mechanical system with nonlinear springs.
For a simple pendulum with a mass evenly distributed along its length and the center of mass located at half the pendulum's length,...
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相关实验视频

Updated: Jul 27, 2025

Wideband Optical Detector of Ultrasound for Medical Imaging Applications
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一个连贯的宽带声源定位使用一个统一的圆形阵列.

Meng Jiang1, Chibuzo Joseph Nnonyelu1, Jan Lundgren1

  • 1Sensible Things that Communicate Research Centre, Mid Sweden University, 852 30 Sundsvall, Sweden.

Sensors (Basel, Switzerland)
|June 10, 2023
PubMed
概括
此摘要是机器生成的。

本研究介绍了一种修改的阵列多重插值 (AMI) 方法用于声音源本地化,显著降低了计算复杂性. 新方法提高了准确性,并使低端处理器上的宽带处理成为可能.

关键词:
阵列多元体的插值插值.抵达方向估计的方向.宽带来源提供宽带资源.

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Simulating Imaging of Large Scale Radio Arrays on the Lunar Surface
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科学领域:

  • 声学 声学 在声学方面
  • 信号处理 信号处理
  • 机器人技术 机器人技术 机器人技术

背景情况:

  • 复杂的应用,如机器人和自动驾驶汽车,需要高效的声音源定位.
  • 现有的方法,如数组多重插值 (AMI) 与多重信号分类 (MUSIC),提供高精度,但存在高计算复杂性.
  • 有需要的声音源本地化技术,平衡准确性与减少计算负载的资源有限的系统.

研究的目的:

  • 为统一的圆形数组 (UCAs) 开发一个修改的数组多重插值 (AMI) 方法,该方法可以降低计算复杂性,同时保持高音源本地化精度.
  • 调查UCA特定的聚焦矩阵在消除贝塞尔函数计算以减少复杂性的有效性.
  • 将拟议方法的性能与iMusic,WS-TOPS和原始AMI等现有算法进行比较.

主要方法:

  • 提出了一个修改的数组多重插值 (AMI) 技术,专门为统一的圆形数组 (UCAs) 量身定制.
  • 引入了UCA特定的聚焦矩阵,以消除对贝塞尔函数计算的需求,从而减少计算复杂性.
  • 在各种场景下,进行了模拟,以将拟议的算法与iMusic,WS-TOPS和原始AMI进行比较.

主要成果:

  • 拟议的修改后的AMI方法表明,与原始AMI相比,计算复杂性降低了.
  • 该算法在不同实验场景中实现了声音源本地化估计准确度的提高.
  • 与原来的AMI方法相比,观察到高达30%的计算时间减少.
  • 开发的方法在准确性和速度方面表现出优于原始AMI的性能.

结论:

  • 对UCAs的修改后的AMI有效地减少了音源定位的计算复杂性.
  • 这一进步允许在低端微处理器上进行高精度,宽带阵列处理,使其适用于资源有限的应用程序.
  • 拟议的方法为增强机器人,自动驾驶汽车和其他复杂系统中的声音源本地化能力提供了实际解决方案.