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IR Frequency Region: Fingerprint Region01:03

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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...
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In IR spectroscopy, signals produced by the X−H bonds (such as C−H, O−H, or N−H) can be observed in the frequency range of  2700–4000 cm–1. The C−H stretching vibration forms sharp bands in the region 2850–3000 cm–1. The presence of the O−H stretching vibration leads to the forming of an absorption band in the frequency range 3650–3200 cm−1. At the same time, N−H stretching can be confirmed by absorption bands in...
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Efficient utilization of Hough transform and orthogonal-triangular decomposition for optical wireless modulation

Safie El-Din Nasr Mohamed, Rasha M Al-Makhlasawy, Muhammed Abdelaziz

    Applied Optics
    |February 24, 2022
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces two novel optical wireless modulation format recognition schemes using image processing techniques like Hough transform and orthogonal-triangular decomposition. These methods achieve high accuracy even at low optical signal-to-noise ratios.

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    Area of Science:

    • Optical Wireless Communication
    • Signal Processing
    • Machine Learning

    Background:

    • Modulation format recognition (MFR) is crucial for optical wireless communication systems.
    • Existing MFR techniques may struggle with performance degradation at low optical signal-to-noise ratios (OSNRs).

    Purpose of the Study:

    • To propose and evaluate two new schemes for optical wireless MFR.
    • To assess the effectiveness of these schemes across various modulation formats and OSNR levels.

    Main Methods:

    • Constellation diagrams of optical signals were generated as images for seven modulation formats (2/4/8/16-PSK, 8/16/32-QAM) at OSNRs from 5 to 30 dB.
    • Two schemes were developed: one using Hough Transform (HT) on images, and another combining orthogonal-triangular decomposition (OTD) with HT.
    • Deep learning classifiers (AlexNet, VGG16, VGG19) were employed for MFR.

    Main Results:

    • Both proposed schemes generated unique signatures for constellation diagrams, enhancing pattern distinguishability.
    • High accuracy in MFR was achieved by both schemes, particularly at lower OSNR values.
    • The study analyzed scheme efficiency across different OSNR levels and modulation formats.

    Conclusions:

    • The proposed OTD and HT-based schemes offer robust optical wireless modulation format recognition.
    • These methods demonstrate significant potential for improving MFR performance in challenging, low-OSNR environments.
    • The use of deep learning classifiers further enhances the accuracy and reliability of the proposed recognition schemes.