A Novel Performance Enhancement Optical Reservoir Computing System Based on Three-Loop Mutual Coupling Structure

被引:4
|
作者
Zhu, Pengjin [1 ]
Wang, Hongxiang [1 ]
Ji, Yuefeng [1 ]
Gao, Guanjun [2 ]
机构
[1] Beijing Univ Posts & Telecommun, Sch Informat & Commun Engn, State Key Lab Informat Photon & Opt Commun, Beijing 100876, Peoples R China
[2] Beijing Univ Posts & Telecommun, Sch Elect Engn, State Key Lab Informat Photon & Opt Commun, Beijing 100876, Peoples R China
基金
中国国家自然科学基金;
关键词
Reservoir computing; electro-optical feedback; three-loop mutual coupling structure; parallel processing; time-series; POLARIZATION DYNAMICS; FEEDBACK;
D O I
10.1109/JLT.2024.3357745
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
We propose and numerically demonstrate a novel performance enhancement optical reservoir computing (RC) system based on a three-loop mutual coupling electro-optical feedback (TLCEO) structure. The nonlinear capability of the proposed RC system is greatly improved by introducing the mutual coupling structure. The proposed system can operate in two modes: single-channel task high-quality processing mode and three-channel tasks parallel processing mode. We evaluate the performance of the proposed TLCEO system by using the chaotic time-series prediction, waveform classification, Nonlinear Autoregressive Moving-average (NARMA) and memory capacity (MC). In single-channel task mode, the proposed system exhibits the best performance in all three tasks compared to other single-node RC systems and multi-node RC systems. The NMSE of Santa-Fe time series prediction, waveform classification and NARMA-10 are only 0.0021, $\text{1.068} \times \text{10}<^>{-9} $ and 0.0658, respectively. Moreover, in three-channel tasks mode, the proposed system has the ability to process three different tasks in parallel, and its performance is the strongest compared to other single-node RC systems. Finally, we analyze in detail the impact of different optical parameters on the performance of the RC system. To sum up, the proposed RC system has both high performance and high efficiency, which has excellent application prospects in communication, sensing and fault prediction in optical networks.
引用
收藏
页码:3151 / 3162
页数:12
相关论文
共 50 条
  • [21] Novel Spike based Reservoir Node Design with High Performance Spike Delay Loop
    Zhao, Chenyuan
    Li, Jialing
    Liu, Lingjia
    Koutha, Lakshmi Sravanthi
    Liu, Jian
    Yi, Yang
    PROCEEDINGS OF THE 3RD ACM INTERNATIONAL CONFERENCE ON NANOSCALE COMPUTING AND COMMUNICATION (ACM NANOCOM 2016), 2016,
  • [22] Performance Enhancement Using Novel Soft Computing AFLC Approach for PV Power System
    Priyadarshi, Neeraj
    Bhoi, Akash Kumar
    Sahana, Sudip Kumar
    Mallick, Pradeep Kumar
    Chakrabarti, Prasun
    COGNITIVE INFORMATICS AND SOFT COMPUTING, 2020, 1040 : 439 - 447
  • [23] Photonic Reservoir Computing based on Optical Filters in a Loop as a High Performance and Low-Power Consumption Equalizer for 100 Gbaud Direct Detection Systems
    Sozos, Kostas
    Bogris, Adonis
    Bienstman, Peter
    Mesaritakis, Charis
    2021 EUROPEAN CONFERENCE ON OPTICAL COMMUNICATION (ECOC), 2021,
  • [24] A Novel Distributed Optical Fiber Sensing System Based on Parallel Computing
    Lu, Lidong
    Liang, Yun
    Li, Binglin
    Guo, Jinghong
    PROCEEDINGS OF THE 2ND INTERNATIONAL CONFERENCE ON COMPUTER AND INFORMATION APPLICATIONS (ICCIA 2012), 2012, : 773 - 776
  • [25] A novel soft-lithography based coupling structure for optical interconnection
    Wu, JH
    Bao, JF
    Wu, X
    ICO20: OPTICAL COMMUNICATION, 2006, 6025
  • [26] Reservoir computing system based on mutually delay-coupled semiconductor lasers with optical feedback
    You, Meiming
    Yang, Xuesong
    Jiang, Dongchen
    Wang, Guoqiang
    OPTICS COMMUNICATIONS, 2024, 562
  • [27] Enhanced memory capacity of a neuromorphic reservoir computing system based on a VCSEL with double optical feedbacks
    Xingxing Guo
    Shuiying Xiang
    Yahui Zhang
    Aijun Wen
    Yue Hao
    Science China Information Sciences, 2020, 63
  • [28] Enhanced memory capacity of a neuromorphic reservoir computing system based on a VCSEL with double optical feedbacks
    Guo, Xingxing
    Xiang, Shuiying
    Zhang, Yahui
    Wen, Aijun
    Hao, Yue
    SCIENCE CHINA-INFORMATION SCIENCES, 2020, 63 (06)
  • [29] Enhanced memory capacity of a neuromorphic reservoir computing system based on a VCSEL with double optical feedbacks
    Xingxing GUO
    Shuiying XIANG
    Yahui ZHANG
    Aijun WEN
    Yue HAO
    Science China(Information Sciences), 2020, 63 (06) : 164 - 175
  • [30] Delay-based reservoir computing: tackling performance degradation due to system response time
    Ortin, Silvia
    Pesquera, Luis
    OPTICS LETTERS, 2020, 45 (04) : 905 - 908