Year
Month
(Peer-Reviewed) Pattern recognition in multi-synaptic photonic spiking neural networks based on a DFB-SA chip
Yanan Han 韩亚楠 ¹, Shuiying Xiang 项水英 ¹, Ziwei Song 宋紫薇 ¹, Shuang Gao 高爽 ¹, Xingxing Guo 郭星星 ¹, Yahui Zhang 张雅慧 ¹, Yuechun Shi 施跃春 ², Xiangfei Chen 陈向飞 ³, Yue Hao 郝跃 ¹
¹ State Key Laboratory of Integrated Service Networks, State Key Discipline Laboratory of Wide Bandgap Semiconductor Technology, Xidian University, Xi'an 710071, China
中国 西安 西安电子科技大学 综合业务网国家重点实验室 宽带隙半导体技术国家重点学科实验室
² Yongjiang Laboratory, Ningbo 315202, China
中国 宁波 甬江实验室
³ Key Laboratory of Intelligent Optical Sensing and Manipulation, Ministry of Education, the National Laboratory of Solid State Microstructures, the College of Engineering and Applied Sciences, Institute of Optical Communication Engineering, Nanjing University, Nanjing 210023, China
中国 南京 南京大学光通信工程研究中心 智能光传感与调控技术教育部重点实验室 固体微结构物理国家重点实验室
Opto-Electronic Science, 2023-11-15
Abstract

Spiking neural networks (SNNs) utilize brain-like spatiotemporal spike encoding for simulating brain functions. Photonic SNN offers an ultrahigh speed and power efficiency platform for implementing high-performance neuromorphic computing. Here, we proposed a multi-synaptic photonic SNN, combining the modified remote supervised learning with delay-weight co-training to achieve pattern classification. The impact of multi-synaptic connections and the robustness of the network were investigated through numerical simulations.

In addition, the collaborative computing of algorithm and hardware was demonstrated based on a fabricated integrated distributed feedback laser with a saturable absorber (DFB-SA), where 10 different noisy digital patterns were successfully classified. A functional photonic SNN that far exceeds the scale limit of hardware integration was achieved based on time-division multiplexing, demonstrating the capability of hardware-algorithm co-computation.
Pattern recognition in multi-synaptic photonic spiking neural networks based on a DFB-SA chip_1
Pattern recognition in multi-synaptic photonic spiking neural networks based on a DFB-SA chip_2
Pattern recognition in multi-synaptic photonic spiking neural networks based on a DFB-SA chip_3
  • Advanced biological imaging techniques based on metasurfaces
  • Yongjae Jo, Hyemi Park, Hyeyoung Yoon, Inki Kim
  • Opto-Electronic Advances
  • 2024-10-31
  • Orthogonal matrix of polarization combinations: concept and application to multichannel holographic recording
  • Shujun Zheng, Jiaren Tan, Hongjie Liu, Xiao Lin, Yusuke Saita, Takanori Nomura, Xiaodi Tan
  • Opto-Electronic Advances
  • 2024-10-23
  • Streamlined photonic reservoir computer with augmented memory capabilities
  • Changdi Zhou, Yu Huang, Yigong Yang, Deyu Cai, Pei Zhou, Kuenyao Lau, Nianqiang Li, Xiaofeng Li
  • Opto-Electronic Advances
  • 2024-10-22
  • High-precision multi-focus laser sculpting of microstructured glass
  • Kang Xu, Peilin Huang, Lingyu Huang, Li Yao, Zongyao Li, Jiantao Chen, Li Zhang, Shaolin Xu
  • Opto-Electronic Advances
  • 2024-10-09
  • Multi-physical field null medium: new solutions for the simultaneous control of EM waves and heat flow
  • Sailing He, Ruili Zhang, Junbo Liang
  • Opto-Electronic Advances
  • 2024-09-30
  • Adaptive decentralized AI scheme for signal recognition of distributed sensor systems
  • Shixiong Zhang, Hao Li, Cunzheng Fan, Zhichao Zeng, Chao Xiong, Jie Wu, Zhijun Yan, Deming Liu, Qizhen Sun
  • Opto-Electronic Advances
  • 2024-09-29
  • Data-driven polarimetric approaches fuel computational imaging expansion
  • Sylvain Gigan
  • Opto-Electronic Advances
  • 2024-09-28
  • An externally perceivable smart leaky-wave antenna based on spoof surface plasmon polaritons
  • Weihan Li, Jia Chen, Shizhao Gao, Lingyun Niu, Jiaxuan Wei, Ruosong Sun, Yaqi Wei, Wenxuan Tang, Tie Jun Cui
  • Opto-Electronic Advances
  • 2024-09-25
  • The possibilities of using a mixture of PDMS and phosphor in a wide range of industry applications
  • Rodrigo Rendeiro, Jan Jargus, Jan Nedoma, Radek Martinek, Carlos Marques
  • Opto-Electronic Advances
  • 2024-09-20
  • Agile cavity ringdown spectroscopy enabled by moderate optical feedback to a quantum cascade laser
  • Qinxue Nie, Yibo Peng, Qiheng Chen, Ningwu Liu, Zhen Wang, Cheng Wang, Wei Ren
  • Opto-Electronic Advances
  • 2024-09-20
  • Genetic algorithm assisted meta-atom design for high-performance metasurface optics
  • Zhenjie Yu, Moxin Li, Zhenyu Xing, Hao Gao, Zeyang Liu, Shiliang Pu, Hui Mao, Hong Cai, Qiang Ma, Wenqi Ren, Jiang Zhu, Cheng Zhang
  • Opto-Electronic Science
  • 2024-09-20
  • Finely regulated luminescent Ag-In-Ga-S quantum dots with green-red dual emission toward white light-emitting diodes
  • Zhi Wu, Leimeng Xu, Jindi Wang, Jizhong Song
  • Opto-Electronic Advances
  • 2024-09-18



  • Optical trapping of optical nanoparticles: Fundamentals and applications                                Ferroelectrically modulate the Fermi level of graphene oxide to enhance SERS response
    About
    |
    Contact
    |
    Copyright © PubCard