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相关概念视频

Fast Fourier Transform01:10

Fast Fourier Transform

299
The Fast Fourier Transform (FFT) is a computational algorithm designed to compute the Discrete Fourier Transform (DFT) efficiently. By breaking down the calculations into smaller, manageable sections, the FFT significantly reduces the computational complexity involved. Direct computation of an N-point DFT requires N2 complex multiplications, whereas the FFT algorithm needs only (N/2)log⁡2N multiplications, offering a much faster performance.
The computational efficiency of the FFT becomes...
299
Upsampling01:22

Upsampling

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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...
224
Reconstruction of Signal using Interpolation01:10

Reconstruction of Signal using Interpolation

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Signal processing techniques are essential for accurately converting continuous signals to digital formats and vice versa. When a continuous signal is sampled with a period T, the resulting sampled signal exhibits replicas of the original spectrum in the frequency domain, spaced at intervals equal to the sampling frequency. To handle this sampled signal, a zero-order hold method can be applied, which creates a piecewise constant signal by retaining each sample's value until the next...
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Aliasing01:18

Aliasing

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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...
128
Properties of DTFT I01:24

Properties of DTFT I

390
In signal processing, Discrete-Time Fourier Transforms (DTFTs) play a critical role in analyzing discrete-time signals in the frequency domain. Various properties of the DTFTs such as linearity, time-shifting, frequency-shifting, time reversal, conjugation, and time scaling help understand and manipulate these signals for different applications.
The linearity property of DTFTs is fundamental. If two discrete-time signals are multiplied by constants a and b respectively, and then combined to...
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Bandpass Sampling01:17

Bandpass Sampling

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In signal processing, bandpass sampling is an effective technique for sampling signals that have most of their energy concentrated within a narrow frequency band. This type of signal is known as a bandpass signal. The key principle of bandpass sampling involves sampling the signal at a rate that is greater than twice the signal's bandwidth to prevent aliasing.
A bandpass signal has a spectrum with a lower frequency limit, denoted as ω1, and an upper frequency limit, denoted as ω2....
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Updated: Jun 21, 2025

X-ray Beam Induced Current Measurements for Multi-Modal X-ray Microscopy of Solar Cells
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高效的光圈填充时间纠正宽带稀疏数组使用改进的可变分数延迟波器.

Jie Gu1, Min Xu1, Wenjing Zhou2

  • 1National Key Laboratory of Electromagnetic Space Security, Chengdu 610036, China.

Sensors (Basel, Switzerland)
|July 13, 2024
PubMed
概括
此摘要是机器生成的。

本研究引入了一种新的多规范化最小值模型,以高效地设计宽带稀疏数组的可变分数延迟过器,显著降低系统复杂性并纠正光圈填充时间.

关键词:
在ADMM算法中,ADMM算法最低的标准标准是最小的标准.变量分数延迟 (VFD) 是一个变量分数延迟.宽带稀疏阵列 宽带稀疏阵列

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科学领域:

  • 信号处理 信号处理
  • 阵列信号处理 阵列信号处理
  • 过器的设计设计

背景情况:

  • 宽带稀疏阵列面临由于线性合的光圈填充时间 (AFT) 挑战.
  • 使用可变分数延迟 (VFD) FIR过器,但导致系统复杂性很高.
  • 现有的minimax型号因过度装配和非独特的解决方案而受到影响.

研究的目的:

  • 开发一种计算效率高的方法来设计VFD FIR过器.
  • 为了减少与宽带稀疏数组中 AFT 校正相关的系统复杂性.
  • 为了提高VFD过器系数的优化.

主要方法:

  • 提出了一种新的多规范化最小值 (MRMM) 模型,该模型包含稀疏表示.
  • 在最小值标准中,用于规范化的是L2规范和多个L1规范.
  • 开发了一种改进的顺序交替方向乘法法 (S-ADMM) 算法来解决非形模型.

主要成果:

  • 该MRMM模型有效地限制了错误函数,减轻了过拟合和非唯一的解决方案.
  • 多个L1规范促进了VFD过器的最佳设计,最小的子过器数量和顺序.
  • 提出的S-ADMM算法有效地解决了非凸的优化问题.

结论:

  • 优化的VFD过器大大降低了系统的复杂性.
  • 拟议的方法有效地纠正宽带稀疏数组中的光圈填充时间.
  • 这种方法为增强宽带稀疏阵列性能提供了一个实际的解决方案.