Reservoir Computing Using Multiple Lasers With Feedback on a Photonic Integrated Circuit

被引:93
作者
Sugano, Chihiro [1 ]
Kanno, Kazutaka [1 ]
Uchida, Atsushi [1 ]
机构
[1] Saitama Univ, Dept Informat & Comp Sci, Saitama 3388570, Japan
基金
日本学术振兴会;
关键词
Reservoir computing; semiconductor lasers; chaos; photonic integrated circuit; information processing; SEMICONDUCTOR-LASERS; PERFORMANCE; CHAOS; IMPLEMENTATION; GENERATION; SYSTEMS;
D O I
10.1109/JSTQE.2019.2929179
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 a scheme for reservoir computing using multiple semiconductor lasers with optical feedback arranged in parallel on a photonic integrated circuit, and we investigate the performance of reservoir computing numerically. The virtual nodes are obtained from the temporal waveforms of the outputs of the parallel reservoir lasers. We test the chaotic time-series prediction task, memory capacity, and nonlinear channel equalization task to investigate the performance of reservoir computing. We found that our scheme using multiple lasers outperforms that using a single laser with multiple delay times. Large memory capacity can also be obtained for the multiple lasers. Finally, we investigate the effect of parameter mismatch of the multiple lasers on reservoir computing performance.
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页数:9
相关论文
共 43 条
[1]   Online Training of an Opto-Electronic Reservoir Computer Applied to Real-Time Channel Equalization [J].
Antonik, Piotr ;
Duport, Francois ;
Hermans, Michiel ;
Smerieri, Anteo ;
Haelterman, Marc ;
Massar, Serge .
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2017, 28 (11) :2686-2698
[2]   Information processing using a single dynamical node as complex system [J].
Appeltant, L. ;
Soriano, M. C. ;
Van der Sande, G. ;
Danckaert, J. ;
Massar, S. ;
Dambre, J. ;
Schrauwen, B. ;
Mirasso, C. R. ;
Fischer, I. .
NATURE COMMUNICATIONS, 2011, 2
[3]   Photonic integrated device for chaos applications in communications [J].
Argyris, A. ;
Hamacher, M. ;
Chlouverakis, K. E. ;
Bogris, A. ;
Syvridis, D. .
PHYSICAL REVIEW LETTERS, 2008, 100 (19)
[4]   Photonic machine learning implementation for signal recovery in optical communications [J].
Argyris, Apostolos ;
Bueno, Julian ;
Fischer, Ingo .
SCIENTIFIC REPORTS, 2018, 8
[5]   Implementation of 140 Gb/s true random bit generator based on a chaotic photonic integrated circuit [J].
Argyris, Apostolos ;
Deligiannidis, Stavros ;
Pikasis, Evangelos ;
Bogris, Adonis ;
Syvridis, Dimitris .
OPTICS EXPRESS, 2010, 18 (18) :18763-18768
[6]   Chaos-on-a-chip secures data transmission in optical fiber links [J].
Argyris, Apostolos ;
Grivas, Evangellos ;
Hamacher, Michael ;
Bogris, Adonis ;
Syvridis, Dimitris .
OPTICS EXPRESS, 2010, 18 (05) :5188-5198
[7]   Parallel photonic information processing at gigabyte per second data rates using transient states [J].
Brunner, Daniel ;
Soriano, Miguel C. ;
Mirasso, Claudio R. ;
Fischer, Ingo .
NATURE COMMUNICATIONS, 2013, 4
[8]   Reinforcement learning in a large-scale photonic recurrent neural network [J].
Bueno, J. ;
Maktoobi, S. ;
Froehly, L. ;
Fischer, I. ;
Jacquot, M. ;
Larger, L. ;
Brunner, D. .
OPTICA, 2018, 5 (06) :756-760
[9]   Conditions for reservoir computing performance using semiconductor lasers with delayed optical feedback [J].
Bueno, Julian ;
Brunner, Daniel ;
Soriano, Miguel C. ;
Fischer, Ingo .
OPTICS EXPRESS, 2017, 25 (03) :2401-2412
[10]  
Dal Bosco A. Karsaklian, 2017, IEEE J SEL TOP QUANT, V23