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时间空间衍射深度神经网络

Junhe Zhou, Haoqian Pu, Jiaxin Yan

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    |February 1, 2024
    PubMed
    概括
    此摘要是机器生成的。

    一个新的时空衍射深度神经网络 (STD2NN) 能够实现先进的信号处理. 这种光学神经网络证明产生复杂的时空信号和光束,就像光学.

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    科学领域:

    • 光学和光子学 在光学和光子学.
    • 人工智能的人工智能
    • 信号处理 信号处理

    背景情况:

    • 时空信号处理对于各种应用至关重要.
    • 现有的方法往往缺乏效率和灵活性.
    • 衍射深度神经网络为光学信号操纵提供了一个有前途的途径.

    研究的目的:

    • 提出和演示一个时空衍射深度神经网络 (STD2NN).
    • 展示STD2NN在生成和处理复杂的时空信号方面的能力.
    • 为培训引入全光反向传播算法.

    主要方法:

    • STD2NN使用格子来进行频率到空间域的转换.
    • 它使用空间透镜和空间光调制器 (SLM) 进行时空相调.
    • 一个全光学反向传播算法用于SLM相调.

    主要成果:

    • 使用STD2NN.成功生成一个时空单词"OPTICA".
    • 一个时空光学 (STOV) 束多重复合器的演示.
    • 将高斯束转换为具有不同拓电荷的STOV波束.

    结论:

    • 拟议的STD2NN是有效的时空信号生成和处理.
    • 全光反传播算法促进了光学网络的高效训练.
    • STD2NN显示了在光通信和信息处理领域的应用潜力.