Time Delay Signature Extraction of Optical Time-Delay Chaos Systems From Short and Noisy Time Series

The optical chaos communication (OCC) can provide physical layer security for high-speed data transmission. In these OCC systems, the time delay signature (TDS) serves as a crucial encryption key. We propose a method based on reservoir computing (RC) network for TDS extraction of OCC systems. The output weight matrix of the RC network provides a numerical representation of nonlinear correlation between a chaotic time series and its time-delayed variants. Then, we can extract TDS by quantifying the features of the weight matrix. The effectiveness is verified by extracting TDS of the two main types of optical time-delay feedback chaos systems. The results demonstrate that, even in cases of strong nonlinearity, noise, and external random disturbance, the TDS can be successfully extracted from time series. Moreover, the required amount of data is significantly reduced in our method.

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Publication Details

Journal
IEEE photonics journal
Published
2024-12-12
DOI
https://doi.org/10.1109/jphot.2024.3516115
Citations
1
Primary Topic
Chaos control and synchronization
Type
article
Field-Weighted Citation Impact
0.28

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article

Time Delay Signature Extraction of Optical Time-Delay Chaos Systems From Short and Noisy Time Series

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1 citations
IEEE photonics journal
Chaos control and synchronization
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article

Time Delay Signature Extraction of Optical Time-Delay Chaos Systems From Short and Noisy Time Series

Chen Shi-yuan, Mengfan Cheng, Xiaojing Gao, Jun Wang, Shuhui Gong, Jing Zhu
article en
1 citations

Abstract

The optical chaos communication (OCC) can provide physical layer security for high-speed data transmission. In these OCC systems, the time delay signature (TDS) serves as a crucial encryption key. We propose a method based on reservoir computing (RC) network for TDS extraction of OCC systems. The output weight matrix of the RC network provides a numerical representation of nonlinear correlation between a chaotic time series and its time-delayed variants. Then, we can extract TDS by quantifying the features of the weight matrix. The effectiveness is verified by extracting TDS of the two main types of optical time-delay feedback chaos systems. The results demonstrate that, even in cases of strong nonlinearity, noise, and external random disturbance, the TDS can be successfully extracted from time series. Moreover, the required amount of data is significantly reduced in our method.

IEEE photonics journalVol. 17(1)
China University of Geosciences (CN), People's Hospital of Bishan District (CN), Wuhan National Laboratory for Optoelectronics (CN), Huazhong University of Science and Technology (CN)
National Natural Science Foundation of China
Climate action
Openalex Percentile: Top 42%
Chaos control and synchronization
0.28
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