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相关概念视频

IR Frequency Region: Fingerprint Region01:03

IR Frequency Region: Fingerprint Region

944
IR spectra are divided into two main regions: the diagnostic region and the fingerprint region. The diagnostic region of the spectrum lies above 1500 cm−1. The absorptions resulting from single-bond vibrations of the N–H, C–H, and O–H stretch at higher wavenumbers and appear on the left side of the spectrum. The stretching absorptions of the C≡C and C≡N occur between 2100–2300 cm−1. In contrast, those arising from stretching absorptions of the...
944
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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相关实验视频

Updated: Jul 22, 2025

Reconstruction of Single-Cell Innate Fluorescence Signatures by Confocal Microscopy
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基于CP分解的可见光指纹数据库恢复算法

Licheng Zhang, Wence Zhang, Xu Bao

    Optics express
    |July 21, 2023
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    此摘要是机器生成的。

    本研究介绍了一种新的算法,用于可见光通信系统的内置定位数据的恢复. 该方法有效地从稀疏的传感器测量中重建指纹数据库,提高准确性.

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    相关实验视频

    Last Updated: Jul 22, 2025

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    Subsurface Defect Localization by Structured Heating Using Laser Projected Photothermal Thermography
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    科学领域:

    • 无线通信无线通信
    • 室内定位系统 室内定位系统
    • 信号处理 信号处理

    背景情况:

    • 可见光通信 (VLC) 为室内定位提供了有前途的解决方案.
    • 基于指纹的可见光定位 (VLP) 需要准确的指纹数据库.
    • 由于成本和空间限制,传感器配置稀缺,导致VLP中的数据丢失.

    研究的目的:

    • 开发一种有效的算法,用于在VLP系统中恢复丢失的指纹数据库信息.
    • 为了应对从稀疏排列的传感器中重建VLP数据的挑战.
    • 为了提高室内定位的准确性和可行性,使用VLC.

    主要方法:

    • 提出了一个时空约束张量完成 (SCTC) 算法.
    • 使用CANDECOMP/PARAFAC (CP) 分解来进行张量重建.
    • 整合了空间和时间约束矩阵以提高恢复准确性,采用无定向图形理论和Toeplitz矩阵.

    主要成果:

    • 该SCTC算法成功地从稀疏的传感器测量中恢复了指纹数据库.
    • 使用空间和时间限制显著提高了恢复数据的准确性.
    • 实验验证证证实了拟议方法的有效性.

    结论:

    • 该SCTC算法提供了一个有效的解决方案,用于重建VLP指纹数据库与稀疏的传感器数据.
    • 这种方法提高了基于VLC的室内定位系统的可靠性和准确性.
    • 这些发现对于克服实际VLP部署中的数据采集挑战至关重要.