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相关概念视频

Discrete-Time Fourier Series01:20

Discrete-Time Fourier Series

The Discrete-Time Fourier Series (DTFS) is a fundamental concept in signal processing, serving as the discrete-time counterpart to the continuous-time Fourier series. It allows for the representation and analysis of discrete-time periodic signals in terms of their frequency components. Unlike its continuous counterpart, which utilizes integrals, the calculation of DTFS expansion coefficients involves summations due to the discrete nature of the signal.
For a discrete-time periodic signal x[n]...
Discrete-time Fourier transform01:26

Discrete-time Fourier transform

The Discrete-Time Fourier Transform (DTFT) is an essential mathematical tool for analyzing discrete-time signals, converting them from the time domain to the frequency domain. This transformation allows for examining the frequency components of discrete signals, providing insights into their spectral characteristics. In the DTFT, the continuous integral used in the continuous-time Fourier transform is replaced by a summation to accommodate the discrete nature of the signal.
One of the notable...
Properties of DTFT I01:24

Properties of DTFT I

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...
Properties of DTFT II01:24

Properties of DTFT II

In the study of discrete-time signal processing, understanding the properties of the Discrete-Time Fourier Transform (DTFT) is crucial for analyzing and manipulating signals in the frequency domain. Several properties, including frequency differentiation, convolution, accumulation, and Parseval's relation, offer powerful tools for signal analysis.
The frequency differentiation property is illustrated by considering a DTFT pair and differentiating both sides with respect to ω. Multiplying by j...
Transmission-Line Differential Equations01:26

Transmission-Line Differential Equations

Transmission lines are essential components of electrical power systems. They are characterized by the distributed nature of resistance (R), inductance (L), and capacitance (C) per unit length. To analyze these lines, differential equations are employed to model the variations in voltage and current along the line.
Line Section Model
A circuit representing a line section of length Δx helps in understanding the transmission line parameters. The voltage V(x) and current i(x) are measured from the...

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相关实验视频

Updated: May 11, 2026

Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging
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Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging

Published on: November 8, 2012

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基于DTI的纤维通道学:为什么不呢?

Dogu Baran Aydogan1,2, Alexander Leemans3, Jessica Dubois4,5

  • 1A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland.

Brain structure & function
|June 5, 2025
PubMed
概括

扩散张力成像 (DTI) 曲谱因其与复杂的大脑结构的局限性而受到争议. 然而,DTI对于临床应用和简单的白质分析仍然很有价值.

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DTI of the Visual Pathway - White Matter Tracts and Cerebral Lesions
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相关实验视频

Last Updated: May 11, 2026

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Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging

Published on: November 8, 2012

26.4K
DTI of the Visual Pathway - White Matter Tracts and Cerebral Lesions
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DTI of the Visual Pathway - White Matter Tracts and Cerebral Lesions

Published on: August 26, 2014

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Fiber Connections of the Supplementary Motor Area Revisited: Methodology of Fiber Dissection, DTI, and Three Dimensional Documentation
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科学领域:

  • 神经成像是一种神经成像.
  • 神经科学是一个神经科学.
  • 医学物理 医学物理

背景情况:

  • 扩散张力成像 (DTI) 是非侵入性大脑白质探索的基石.
  • DTI中的张量模型在准确重建复杂的白质纤维配置方面存在局限性.

研究的目的:

  • 总结一场关于使用DTI用于曲谱的可接受性辩论.
  • 探索先进导向模型和基于DTI的曲谱学之间的权衡.

主要方法:

  • 总结了2024年特拉克特-阿纳特撤退辩论中的关键点.
  • 讨论先进导向模型与DTI的优势.

主要成果:

  • 先进的模型提供了更完整,更准确的白质路径重建.
  • 在特定的临床环境和更简单的纤维架构中,基于DTI的曲谱学仍然具有价值.

结论:

  • 对于DTI的可接受性是取决于应用程序.
  • 一种细微的方法是必要的,在评估张量模型实用性时考虑具体的用例.