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相关概念视频

Impulse Response01:17

Impulse Response

257
The impulse response is the system's reaction to an input impulse. In an RC circuit, the voltage source is the input, and the capacitor's voltage is the output. The system's state and output response before and after input excitation are distinctly defined.
Kirchhoff's law forms an input signal equation, with the capacitor's current and voltage providing the output. Substituting the current and dividing by RC yields a differential equation. The output for an impulse input is...
257
Deconvolution01:20

Deconvolution

160
Deconvolution, also known as inverse filtering, is the process of extracting the impulse response from known input and output signals. This technique is vital in scenarios where the system's characteristics are unknown, and they must be inferred from the observable signals.
Deconvolution involves several mathematical techniques to derive the impulse response. One common approach is polynomial division. In this method, the input and output sequences are treated as coefficients of...
160
Impact01:30

Impact

146
Impact occurs when two bodies collide, leading to the application of impulsive forces between them. Analyzing impact mechanics involves considering two colliding particles moving along a line known as the line of impact, which passes through their centers and is perpendicular to the contact plane.
When particles with different initial velocities collide, they induce deformation by applying equal and opposite impulses. At the point of maximum deformation, the particles move together with...
146
Principle of Linear Impulse and Momentum for a Single Particle: Problem Solving01:23

Principle of Linear Impulse and Momentum for a Single Particle: Problem Solving

201
Consider a wooden box and a cylinder of known masses m1 and m2, respectively,  hanging from a ceiling with the help of a massless pulley system.
201
Impulse01:13

Impulse

18.9K
According to Newton’s second law of motion, the rate of change of the momentum of an object is the net external force acting on it. The total change in momentum between two timepoints thus depends on both the external force acting on it and the time over which it acts. Describing this mathematically, the total change of an object’s motion is proportional to the force vector and the time over which it is applied. This product is called impulse.
Additionally, it can be shown that the...
18.9K
Principle of Linear Impulse and Momentum for a Single Particle01:20

Principle of Linear Impulse and Momentum for a Single Particle

665
Linear momentum is a fundamental concept in physics that describes the motion of an object. It is a vector quantity, having a magnitude equal to the product of its mass and its velocity, and direction along the object's velocity. On the other hand, linear impulse, also known as momentum impulse, is a concept in physics related to the change in the linear momentum of an object. Impulse is a vector quantity defined as the product of force and the time over which the force is applied.
Delving...
665

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Updated: Jul 3, 2025

Simulation of Human-induced Vibrations Based on the Characterized In-field Pedestrian Behavior
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Simulation of Human-induced Vibrations Based on the Characterized In-field Pedestrian Behavior

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房间冲动响应重建与物理知情深度学习.

Xenofon Karakonstantis1, Diego Caviedes-Nozal2, Antoine Richard3

  • 1Acoustic Technology, Department of Electrical & Photonics Engineering, Technical University of Denmark, Kongens Lyngby, Denmark.

The Journal of the Acoustical Society of America
|February 11, 2024
PubMed
概括
此摘要是机器生成的。

这项研究引入了一个基于物理的神经网络,用于使用有限的声学数据重建室内声音场. 该方法准确地估计了声压,粒子速度和能量流,在早期冲动响应重建中表现优于现有的技术.

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A Simple Stimulatory Device for Evoking Point-like Tactile Stimuli: A Searchlight for LFP to Spike Transitions
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科学领域:

  • 声学 声学 在声学方面
  • 计算物理学的计算物理.
  • 机器学习是机器学习.

背景情况:

  • 准确的声场重建对于建筑声学和音频工程至关重要.
  • 传统方法通常需要进行广泛的测量或复杂的模拟.
  • 基于物理学的神经网络 (PINNs) 通过将物理定律集成到机器学习模型中,提供了一种新的方法.

研究的目的:

  • 开发和评估PINN以估计和重建一个房间内的完整声场.
  • 评估网络对超出声压的声能流量进行表征的能力.
  • 调查PINNs用于增强声学模拟的潜力,并将其与现有的重建方法进行比较.

主要方法:

  • 利用在有限的实验室冲动响应上训练的物理信息神经网络.
  • 将波方程纳入神经网络架构中的声音传播物理模型.
  • 估计声压,粒子速度和声强度,以表征声场.
  • 将PINN方法与数据驱动和基于波的回归方法进行比较,用于声场重建.

主要成果:

  • PINN成功地估计了粒子速度和强度,以最小的测量提供了声音场的全面表征.
  • 该网络证明了在低推理时间的无网格声场映射方面的熟练程度,这表明了改进声学模拟的潜力.
  • 对比分析表明,PINN在重建房间冲动响应的早期部分方面表现出色.
  • 拟议的方法在时间域中实现了完整的声场表征.

结论:

  • 基于物理学的神经网络为声场估计和重建提供了有效和高效的方法.
  • 这种方法为声学分析,模拟和理解声学能量流提供了一个强大的工具.
  • 与当前技术相比,PINN方法具有显著的优势,特别是在早期冲动响应重建方面.