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Ultraviolet–visible (UV–visible or UV–Vis) spectroscopy is an analytical technique that investigates the interaction between matter and UV–Vis light within the electromagnetic spectrum. This method is widely used for its versatility, simplicity, and relatively quick data acquisition, making it valuable for both qualitative and quantitative analysis. When UV–Vis radiation passes through a material,  molecules absorb light depending on the energy required for...
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To calculate the flow rate for a trapezoidal channel, first, identify the bottom width, side slope, and flow depth of the channel. The cross-sectional area (A) corresponding to the depth of flow (y), channel bottom width (B), and side slope (θ) is determined by:Next, calculate the wetted perimeter, which includes the bottom width and the sloped side lengths in contact with the water. Using the values of the cross-sectional area and the wetted perimeter, determine the hydraulic radius by...
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在UVLC系统中的调制格式识别基于库存计算与坐标转换和折叠算法.

Fujie Li, Xianhao Lin, Jianyang Shi

    Optics express
    |June 29, 2023
    PubMed
    概括

    本研究介绍了一种轻量储计算 (RC) 方法,用于在水下可见光通信中进行调制格式识别 (MFR). 与神经网络相比,高效的RC方法可以实现高精度,并显著降低计算成本.

    科学领域:

    • 光学通信是指光学通信.
    • 信号处理 信号处理
    • 机器学习 机器学习

    背景情况:

    • 调制格式识别 (MFR) 对自适应光学系统至关重要.
    • 基于深度学习的MFR算法取得了成功,但计算密集,特别是在复杂的水下可见光通信 (UVLC) 通道中.
    • 复杂的神经网络 (NN) 结构阻碍了实时处理和UVLC中的高效分配.

    研究的目的:

    • 为UVLC系统提出一种轻量级和高效的MFR方法.
    • 为了减少计算复杂性和提高MFR的处理速度.
    • 调查在UVLC中MFR任务的储库计算 (RC) 的性能.

    主要方法:

    • 开发了一种基于储库计算 (RC) 的方法,可训练参数显著减少 (0.3%的NN方法).
    • 实施了先进的特征提取算法,包括坐标转换和折叠算法,以提高RC性能.
    • 在六个调制格式上测试了RC方法:OK,4QAM,8QAM-DIA,8QAM-CIR,16APSK和16QAM.

    主要成果:

    • 提出的基于RC的MFR方法可以在几秒钟内实现训练时间.
    • 对于大多数调制格式,识别精度超过了90%,在不同的LED引脚电压下达到接近100%.

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  • 该方法在UVLC中证明了MFR的高效率和准确性.

    • 结论:

    • 储计算为UVLC中的MFR提供了一个计算效率高,准确的替代方案.
    • 像坐标转换和折叠这样的特征提取技术在提高MFR的RC性能方面是有效的.
    • 该研究为设计有效的RC系统提供了指导,为MFR应用程序平衡精度和计算成本.