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相关概念视频

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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2D NMR: Heteronuclear Single-Quantum Correlation Spectroscopy (HSQC)01:19

2D NMR: Heteronuclear Single-Quantum Correlation Spectroscopy (HSQC)

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Heteronuclear single-quantum correlation spectroscopy (HSQC) is a 2D NMR technique that reveals one-bond correlations between hydrogen and a heteronucleus. The HSQC experiment is similar to the heteronuclear correlation experiment (HETCOR) but is more sensitive. In the HSQC spectrum, the proton chemical shift is plotted on the horizontal F2 axis, while the 13C chemical shift is plotted on the vertical F1 axis. The corresponding proton and 13C spectra are also shown. The HSQC contour plot does...
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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...
136
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...
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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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Sampling Theorem01:15

Sampling Theorem

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In signal processing, the analysis of continuous-time signals, denoted as x(t), often involves sampling techniques to convert these signals into discrete-time signals. This process is essential for digital representation and manipulation. A critical component in sampling is the train of impulses, characterized by the sampling interval and the sampling frequency. The relationship between these parameters and the original signal's properties dictates the success of the sampling process.
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使用双阶段曲分析对亚和声量化的验证.

Itsuki Kitayama1, Kiyohito Hosokawa2, Shinobu Iwaki3

  • 1Department of Otorhinolaryngology and Head & Neck Surgery, Osaka University Graduate School of Medicine, Osaka, Japan.

Journal of voice : official journal of the Voice Foundation
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PubMed
概括

量化声音粗仍然是一个挑战. 虽然两阶段的曲分析显示出有希望的结果,但它需要进一步开发,以便在语音分析中准确检测次声和粗度.

关键词:
声学分析 声学分析这就是Cepstrum.二重音声症 (Diplophonia) 是一种失声症.粗性 粗性 粗性亚声乐是什么意思 亚声乐是什么意思

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科学领域:

  • 声音的声学分析.
  • 语音病理学 语音病理学
  • 定量语音评价 定量语音评价

背景情况:

  • 声音粗是声的一个关键组成部分,通常与复杂的声学结构 (如亚和声器) 相关.
  • 由于这些复杂性,现有的定量工具很难准确地测量粗度.
  • 双阶段塞普斯特拉分析为量化粗度提供了一个潜在的方法.

研究的目的:

  • 为了提高两阶段塞普斯特拉分析对声部粗度测量的准确性.
  • 为了研究声音粗度和亚和声之间的关系.
  • 在声学分析中评估定制音调设置的诊断能力.

主要方法:

  • 一项回顾性研究分析了455名参与者的语音记录 (语音障碍者和正常对照).
  • 两阶段的 cepstral 分析是使用语音失声的分析和声音和Prat 软件进行的.
  • 从窄带光谱图进行视觉定量,用于验证和可靠性评估.

主要成果:

  • 两阶段的分析表明软件程序之间存在很高的相关性 (r=0.963).
  • 从光谱图中测量出的亚声波显示出良好的可靠性和与感知粗度的强烈相关性.
  • 尽管有定制的音调设置,但两阶段的 cepstral 分析显示了粗度和亚声调的微弱至中度相关性.

结论:

  • 两阶段的 cepstral 分析显示,即使在调音定制下,在检测次和声和粗度方面也有有限的改善.
  • 基于谱图的亚声波分析证实了亚声波和粗之间存在强烈的联系.
  • 进一步开发声学分析参数对于准确的亚和声和粗度检测至关重要.