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Parallel information processing using a reservoir computing system based on mutually coupled semiconductor lasers

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Via the nonlinear channel equalization and the Santa-Fe time series prediction, the parallel processing capability of a reservoir computing (RC) system based on two mutually coupled semiconductor lasers is demonstrated numerically. The results show that, for parallel processing the prediction tasks of two Santa-Fe time series with rates of 0.25 GSa/s, the minimum prediction errors are 3.8 × 10−5 and 4.4 × 10−5, respectively. For parallel processing two nonlinear channel equalization tasks, the minimum symbol error rates (SERs) are 3.3 × 10−4 for both tasks. For parallel processing a nonlinear channel equalization and a Santa-Fe time series prediction, the minimum SER is 6.7 × 10−4 for nonlinear channel equalization, and the minimum prediction error is 4.6 × 10−5 for Santa-Fe time series prediction.

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This work was supported in part by the National Natural Science Foundation of China under Grant 61575163, Grant 61775184, and Grant 61875167, in part by the Natural Science Foundation of Inner Mongolia Autonomous Region of china under Grant 2019MS06022, and in part by the Postgraduate Research and Innovation Project of Chongqing Municipality under Grant CYB19087.

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Correspondence to G. Q. Xia or Z. M. Wu.

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Hou, Y.S., Xia, G.Q., Jayaprasath, E. et al. Parallel information processing using a reservoir computing system based on mutually coupled semiconductor lasers. Appl. Phys. B 126, 40 (2020). https://doi.org/10.1007/s00340-019-7351-4

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