Search Results - "Zang, Yubin"

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  1. 1

    Photonic machine learning with on-chip diffractive optics by Fu, Tingzhao, Zang, Yubin, Huang, Yuyao, Du, Zhenmin, Huang, Honghao, Hu, Chengyang, Chen, Minghua, Yang, Sigang, Chen, Hongwei

    Published in Nature communications (05-01-2023)
    “…Machine learning technologies have been extensively applied in high-performance information-processing fields. However, the computation rate of existing…”
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    Journal Article
  2. 2

    Implicit Adaptive Moment Estimation Method for On-Chip Metasurface Design and Optimization by Zang, Yubin, Li, Simin, Zhang, Fangzheng, Zhang, Zuxing, Chen, Hongwei

    Published in IEEE photonics technology letters (15-10-2024)
    “…In this letter, we present a new implicit optimizing method for optical device's or system's design and optimization. This method, derived from the traditional…”
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    Journal Article
  3. 3

    On-chip photonic diffractive optical neural network based on a spatial domain electromagnetic propagation model by Fu, Tingzhao, Zang, Yubin, Huang, Honghao, Du, Zhenmin, Hu, Chengyang, Chen, Minghua, Yang, Sigang, Chen, Hongwei

    Published in Optics express (27-09-2021)
    “…An integrated physical diffractive optical neural network (DONN) is proposed based on a standard silicon-on-insulator (SOI) substrate. This DONN has compact…”
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    Journal Article
  4. 4

    Electro-Optical Neural Networks Based on Time-Stretch Method by Zang, Yubin, Chen, Minghua, Yang, Sigang, Chen, Hongwei

    “…In this paper, a novel architecture of electro-optical neural networks based on the time-stretch method is proposed and numerically simulated. By stretching…”
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    Journal Article
  5. 5

    Principle-Driven Fiber Transmission Model Based on PINN Neural Network by Zang, Yubin, Yu, Zhenming, Xu, Kun, Lan, Xingzeng, Chen, Minghua, Yang, Sigang, Chen, Hongwei

    Published in Journal of lightwave technology (15-01-2022)
    “…In this paper, a novel principle-driven fiber transmission model based on physical induced neural network (PINN) is proposed. Unlike data-driven models which…”
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    Journal Article
  6. 6

    Data-driven fiber model based on the deep neural network with multi-head attention mechanism by Zang, Yubin, Yu, Zhenming, Xu, Kun, Chen, Minghua, Yang, Sigang, Chen, Hongwei

    Published in Optics express (19-12-2022)
    “…In this paper, we put forward a data-driven fiber model based on the deep neural network with multi-head attention mechanism. This model, which predicts signal…”
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    Journal Article
  7. 7

    Multi-Span Long-Haul Fiber Transmission Model Based on Cascaded Neural Networks With Multi-Head Attention Mechanism by Zang, Yubin, Yu, Zhenming, Xu, Kun, Chen, Minghua, Yang, Sigang, Chen, Hongwei

    Published in Journal of lightwave technology (01-10-2022)
    “…In this paper, a novelty fiber transmission model consisting of cascaded neural networks with the multi-head attention mechanism has been put forward to solve…”
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    Journal Article
  8. 8

    Optoelectronic convolutional neural networks based on time-stretch method by Zang, Yubin, Chen, Minghua, Yang, Sigang, Chen, Hongwei

    Published in Science China. Information sciences (01-02-2021)
    “…In this paper, a new architecture of optoelectronic convolutional neural networks (CNNs) based on time-stretch method is proposed. In this loop-shaped…”
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    Journal Article
  9. 9
  10. 10

    Fiber neural networks for the intelligent optical fiber communications by Zang, Yubin, Zhang, Zuxing, Li, Simin, Zhang, Fangzheng, Chen, Hongwei

    Published 07-08-2024
    “…Optical neural networks have long cast attention nowadays. Like other optical structured neural networks, fiber neural networks which utilize the mechanism of…”
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    Journal Article
  11. 11

    Classification and Recognition of Fiber Optic Vibration Sensing Signals Based on Wavelet Packet Decomposition and 1D-CNN Algorithm by Chang, Hongqiang, Gu, Yu, Zang, Yubin, Wan, Hongdan

    “…Algorithm using wavelet packet decomposition and 1D convolutional neural network is proposed to improve recognition accuracy of distributed fiber optic…”
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    Conference Proceeding
  12. 12

    Fiber Transmission Model with Parameterized Inputs based on GPT-PINN Neural Network by Zang, Yubin, Hua, Boyu, Lin, Zhipeng, Zhang, Fangzheng, Li, Simin, Zhang, Zuxing, Chen, Hongwei

    Published 19-08-2024
    “…In this manuscript, a novelty principle driven fiber transmission model for short-distance transmission with parameterized inputs is put forward. By taking…”
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    Journal Article
  13. 13

    Principle Driven Parameterized Fiber Model based on GPT-PINN Neural Network by Zang, Yubin, Hua, Boyu, Tang, Zhenzhou, Lin, Zhipeng, Zhang, Fangzheng, Li, Simin, Zhang, Zuxing, Chen, Hongwei

    Published 19-08-2024
    “…In cater the need of Beyond 5G communications, large numbers of data driven artificial intelligence based fiber models has been put forward as to utilize…”
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    Journal Article
  14. 14

    Principle-driven Fiber Transmission Model based on PINN Neural Network by Zang, Yubin, Yu, Zhenming, Xu, Kun, Lan, Xingzeng, Chen, Minghua, Yang, Sigang, Chen, Hongwei

    Published 24-08-2021
    “…In this paper, a novel principle-driven fiber transmission model based on physical induced neural network (PINN) is proposed. Unlike data-driven models which…”
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    Journal Article
  15. 15

    High Accuracy Non Ambiguity ToF Lidar System Based on Pseudo-Random Noise Code and Phase Detection Method by Zang, Yubin, Chen, Hongwei, Yang, Sigang, Chen, Minghua

    “…By utilizing PRN code and phase detection method under 1GHz sub-carrier modulation, an improved ToF Lidar is proposed which achieves millimeter accuracy under…”
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    Conference Proceeding
  16. 16

    Electro-optical Neural Networks based on Time-stretch Method by Zang, Yubin, Chen, Minghua, Yang, Sigang, Chen, Hongwei

    Published 12-09-2019
    “…In this paper, a novel architecture of electro-optical neural networks based on the time-stretch method is proposed and numerically simulated. By stretching…”
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    Journal Article
  17. 17

    Universal Fiber Models based on PINN Neural Network by Zang, Yubin, Yu, Zhenming, Xu, Kun, Chen, Minghua, Yang, Sigang, Chen, Hongwei

    “…We apply the PINN neural network in fields of communication fiber model to provide another way of researching pulse and signal evolution. This method can have…”
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    Conference Proceeding