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 mapping relationship between the system output time series and its delay variants is learned by the RC network. Then, the convergence performance of the RC network is measured and used for TDS extraction. The effectiveness is verified by extracting TDS of the two main types of optical time-delay fe

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[1] Shuhui Gong, "Time delay signature extraction of optical time-delay chaos systems from short and noisy time series", IEEE Dataport, 2024. [Online]. Available: http://dx.doi.org/10.21227/rsrm-yy19. Accessed: Jul. 22, 2024.
@data{rsrm-yy19-24,
doi = {10.21227/rsrm-yy19},
url = {http://dx.doi.org/10.21227/rsrm-yy19},
author = {Shuhui Gong },
publisher = {IEEE Dataport},
title = {Time delay signature extraction of optical time-delay chaos systems from short and noisy time series},
year = {2024} }
TY - DATA
T1 - Time delay signature extraction of optical time-delay chaos systems from short and noisy time series
AU - Shuhui Gong
PY - 2024
PB - IEEE Dataport
UR - 10.21227/rsrm-yy19
ER -
Shuhui Gong. (2024). Time delay signature extraction of optical time-delay chaos systems from short and noisy time series. IEEE Dataport. http://dx.doi.org/10.21227/rsrm-yy19
Shuhui Gong, 2024. Time delay signature extraction of optical time-delay chaos systems from short and noisy time series. Available at: http://dx.doi.org/10.21227/rsrm-yy19.
Shuhui Gong. (2024). "Time delay signature extraction of optical time-delay chaos systems from short and noisy time series." Web.
1. Shuhui Gong. Time delay signature extraction of optical time-delay chaos systems from short and noisy time series [Internet]. IEEE Dataport; 2024. Available from : http://dx.doi.org/10.21227/rsrm-yy19
Shuhui Gong. "Time delay signature extraction of optical time-delay chaos systems from short and noisy time series." doi: 10.21227/rsrm-yy19