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相关概念视频

Linear Approximation in Time Domain01:21

Linear Approximation in Time Domain

81
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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Linear Approximation in Frequency Domain01:26

Linear Approximation in Frequency Domain

89
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....
89
Downsampling01:20

Downsampling

154
When considering a sampled sequence with zero values between sampling instants, one can replace it by taking every N-th value of the sequence. At these integer multiples of N, the original and sampled sequences coincide. This process, known as decimation, involves extracting every N-th sample from a sequence, thereby creating a more efficient sequence.
The Fourier transform of the decimated sequence reveals a combination of scaled and shifted versions of the original spectrum. This...
154
Upsampling01:22

Upsampling

232
Managing signal sampling rates is essential in digital signal processing to maintain signal integrity. A decimated signal, characterized by a reduced frequency range due to its lower sampling rate, can be upsampled by inserting zeros between each sample. This upsampling process expands the original spectrum and introduces repeated spectral replicas at intervals dictated by the new Nyquist frequency. To refine this zero-inserted sequence, it is passed through a lowpass filter with a cutoff...
232
Aliasing01:18

Aliasing

133
Accurate signal sampling and reconstruction are crucial in various signal-processing applications. A time-domain signal's spectrum can be revealed using its Fourier transform. When this signal is sampled at a specific frequency, it results in multiple scaled replicas of the original spectrum in the frequency domain. The spacing of these replicas is determined by the sampling frequency.
If the sampling frequency is below the Nyquist rate, these replicas overlap, preventing the original...
133
¹³C NMR: ¹H–¹³C Decoupling01:04

¹³C NMR: ¹H–¹³C Decoupling

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The probability of having two carbon-13 atoms next to each other is negligible because of the low natural abundance of carbon-13. Consequently, peak splitting due to carbon-carbon spin-spin coupling is not observed in spectra. However, protons up to three sigma bonds away split the carbon signal according to the n+1 rule, resulting in complicated spectra.
A broadband decoupling technique is used to simplify these complex, sometimes overlapping, signals. Broadband decoupling relies on a...
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Updated: Jun 28, 2025

Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform
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一个低复杂度的基于声学的3D DoA估计与零循环和.

Rigel Procópio Fernandes1, José Antonio Apolinário1,2, José Manoel de Seixas3

  • 1Program of Defense Engineering, Military Institute of Engineering (IME), Rio de Janeiro 22290-270, Brazil.

Sensors (Basel, Switzerland)
|April 13, 2024
PubMed
概括

本研究引入了一种两阶段的到达方向 (DoA) 估计方法,该方法使用交叉相关的二级峰值. 这种精细的方法在声学无人机检测中实现了94.0%的准确性.

关键词:
在DoA估计的估计.时间延迟估计时间延迟估计零周期总和是零周期总和.

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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
  • 阵列信号处理 阵列信号处理

背景情况:

  • 准确的到达方向 (DoA) 估计对于监视,安全和空间音频至关重要.
  • 现有的方法可能会在复杂的声学环境中扎,并识别所有相关信号特征.

研究的目的:

  • 开发一种创新的,复杂性降低的DoA估计方法.
  • 通过利用交叉相关函数中的二次峰值来提高DoA的准确性.
  • 为了验证该方法在具有挑战性的声学场景中的有效性,例如无人机检测.

主要方法:

  • 提出了一种两阶段的方法,从一个低复杂度的零周期总和 (ZCS) 成本函数开始,用于详尽的时间延迟搜索.
  • 第二阶段在ZCS函数识别的有希望的时间延迟组合子集上使用最小平方 (LS) 解决方案.
  • 该方法应用于基于声学的无人机DoA估计,使用四个麦克风阵列.

主要成果:

  • 仅使用ZCS方法就能达到89.4%±2.7%的准确度.
  • 结合的ZCS和LS方法显著提高了准确度,达到94.0%±3.1%.
  • 该方法在模拟和真实世界声学数据上都表现出了有效性.

结论:

  • 拟议的两阶段DoA估计方法为复杂的声学环境提供了可行的替代方案.
  • 利用二次交叉相关性峰值可以提高DoA估计的准确性.
  • 对于关键的DoA应用程序,ZCS-LS方法提供了一个计算效率高且准确的解决方案.