Literature DB >> 27137303

Laser dynamical reservoir computing with consistency: an approach of a chaos mask signal.

Joma Nakayama, Kazutaka Kanno, Atsushi Uchida.   

Abstract

We numerically investigate reservoir computing based on the consistency of a semiconductor laser subjected to optical feedback and injection. We introduce a chaos mask signal as an input temporal mask for reservoir computing and perform a time-series prediction task. We compare the errors of the task obtained from the chaos mask signal with those obtained from other digital and analog masks. The performance of the prediction task can be improved by using the chaos mask signal due to complex dynamical response.

Year:  2016        PMID: 27137303     DOI: 10.1364/OE.24.008679

Source DB:  PubMed          Journal:  Opt Express        ISSN: 1094-4087            Impact factor:   3.894


  10 in total

1.  Spintronic reservoir computing without driving current or magnetic field.

Authors:  Tomohiro Taniguchi; Amon Ogihara; Yasuhiro Utsumi; Sumito Tsunegi
Journal:  Sci Rep       Date:  2022-06-23       Impact factor: 4.996

2.  Enhancing Performance of Reservoir Computing System Based on Coupled MEMS Resonators.

Authors:  Tianyi Zheng; Wuhao Yang; Jie Sun; Xingyin Xiong; Zheng Wang; Zhitian Li; Xudong Zou
Journal:  Sensors (Basel)       Date:  2021-04-23       Impact factor: 3.576

3.  Quantitative identification of dynamical transitions in a semiconductor laser with optical feedback.

Authors:  C Quintero-Quiroz; J Tiana-Alsina; J Romà; M C Torrent; C Masoller
Journal:  Sci Rep       Date:  2016-11-18       Impact factor: 4.379

4.  Photonic machine learning implementation for signal recovery in optical communications.

Authors:  Apostolos Argyris; Julián Bueno; Ingo Fischer
Journal:  Sci Rep       Date:  2018-05-31       Impact factor: 4.379

5.  Research on Weak Fault Extraction Method for Alleviating the Mode Mixing of LMD.

Authors:  Lin Zhang; Zhijian Wang; Long Quan
Journal:  Entropy (Basel)       Date:  2018-05-21       Impact factor: 2.524

6.  Parameters optimization method for the time-delayed reservoir computing with a nonlinear duffing mechanical oscillator.

Authors:  T Y Zheng; W H Yang; J Sun; X Y Xiong; Z T Li; X D Zou
Journal:  Sci Rep       Date:  2021-01-13       Impact factor: 4.379

7.  Fast physical repetitive patterns generation for masking in time-delay reservoir computing.

Authors:  Apostolos Argyris; Janek Schwind; Ingo Fischer
Journal:  Sci Rep       Date:  2021-03-23       Impact factor: 4.379

8.  Photonic reinforcement learning based on optoelectronic reservoir computing.

Authors:  Kazutaka Kanno; Atsushi Uchida
Journal:  Sci Rep       Date:  2022-03-08       Impact factor: 4.996

9.  Dynamic Nonlinear Behavior of Ionic Liquid-Based Reservoir Computing Devices.

Authors:  Takuma Matsuo; Dan Sato; Sang-Gyu Koh; Hisashi Shima; Yasuhisa Naitoh; Hiroyuki Akinaga; Toshiyuki Itoh; Toshiki Nokami; Masakazu Kobayashi; Kentaro Kinoshita
Journal:  ACS Appl Mater Interfaces       Date:  2022-07-26       Impact factor: 10.383

10.  Guiding principle of reservoir computing based on "small-world" network.

Authors:  Ken-Ichi Kitayama
Journal:  Sci Rep       Date:  2022-10-06       Impact factor: 4.996

  10 in total

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