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相关概念视频

Deconvolution01:20

Deconvolution

180
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...
180
Reconstruction of Signal using Interpolation01:10

Reconstruction of Signal using Interpolation

225
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...
225
Convolution Properties II01:17

Convolution Properties II

224
The important convolution properties include width, area, differentiation, and integration properties.
The width property indicates that if the durations of input signals are T1 and T2, then the width of the output response equals the sum of both durations, irrespective of the shapes of the two functions. For instance, convolving two rectangular pulses with durations of 2 seconds and 1 second results in a function with a width of 3 seconds.
The area property asserts that the area under the...
224
Convolution Properties I01:20

Convolution Properties I

170
Convolution computations can be simplified by utilizing their inherent properties.
The commutative property reveals that the input and the impulse response of an LTI (Linear Time-Invariant) system can be interchanged without affecting the output:
170
¹³C NMR: Distortionless Enhancement by Polarization Transfer (DEPT)01:20

¹³C NMR: Distortionless Enhancement by Polarization Transfer (DEPT)

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When proton-coupled carbon-13 spectra are simplified by a broadband proton decoupling technique, structural information about the coupled protons is lost. Distortionless enhancement by polarization transfer (DEPT) is a technique that provides information on the number of hydrogens attached to each carbon in a molecule. While the DEPT experiment utilizes complex pulse sequences, the pulse delay and flip angle are specifically manipulated. The resulting signals have different phases depending on...
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Region of Convergence of Laplace Tarnsform01:20

Region of Convergence of Laplace Tarnsform

577
The Region of Convergence (ROC) is a fundamental concept in signal processing and system analysis, particularly associated with the Laplace transform. The ROC represents an area in the complex plane where the Laplace transform of a given signal converges, determining the transform's applicability and utility.
Consider a decaying exponential signal that begins at a specific time. When deriving its Laplace transform, the time-domain variable is replaced with a complex variable. This...
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相关实验视频

Updated: Jul 15, 2025

Determining 3D Flow Fields via Multi-camera Light Field Imaging
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Determining 3D Flow Fields via Multi-camera Light Field Imaging

Published on: March 6, 2013

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维格纳分布 解卷化 适应现场影像学 重建

Arya Bangun1, Paul F Baumeister2, Alexander Clausen1

  • 1Ernst Ruska-Centre for Microscopy and Spectroscopy with Electrons, Forschungszentrum Jülich, 52425 Jülich, Germany.

Microscopy and microanalysis : the official journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada
|September 25, 2023
PubMed
概括

我们开发了一种更快的维格纳分布解卷 (WDD) 方法,用于实时拍摄. 这种技术可以在数据采集过程中实时重建样本传输功能,提高速度和减少内存使用.

关键词:
维格纳分布的解卷分解现场加工 现场加工图形摄影 (ptychography) 是一种图形摄影技术.重建的重建的重建.

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Live Images of GLUT4 Protein Trafficking in Mouse Primary Hypothalamic Neurons Using Deconvolution Microscopy
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相关实验视频

Last Updated: Jul 15, 2025

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科学领域:

  • 电子显微镜的电子显微镜
  • 图像处理 图像处理
  • 材料科学是一种材料科学.

背景情况:

  • 隐形摄影是一种强大的无镜头成像技术.
  • 在ptychography中实时重建是计算密集的.
  • 目前的方法限制在采集过程中逐渐显示标本属性.

研究的目的:

  • 为了引入一个修改的维格纳分布解卷 (WDD) 现场拍摄.
  • 为了使在数据采集过程中逐步重建和显示样本传输功能.
  • 为了减少实时处理的计算复杂性和内存消耗.

主要方法:

  • 维格纳分布解卷 (WDD) 的重构.
  • 应用一个缩小尺寸的技术.
  • 数字模拟用于验证.

主要成果:

  • 保持高质量的样本转移功能重建.
  • 显著降低了内存消耗和提高了处理速度.
  • 扫描传输电子显微镜 (STEM) 数据集的实时处理的可行性.

结论:

  • 经过修改的WDD可以实现高效的实时图形重建.
  • 这种方法适用于需要实时图解的各种领域.
  • 这种方法增强了活体分析的图形学的实用性.