Literature DB >> 33758334

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

Apostolos Argyris1, Janek Schwind2,3, Ingo Fischer2.   

Abstract

Albeit the conceptual simplicity of hardware reservoir computing, the various implementation schemes that have been proposed so far still face versatile challenges. The conceptually simplest implementation uses a time delay approach, where one replaces the ensemble of nonlinear nodes with a unique nonlinear node connected to a delayed feedback loop. This simplification comes at a price in other parts of the implementation; repetitive temporal masking sequences are required to map the input information onto the diverse states of the time delay reservoir. These sequences are commonly introduced by arbitrary waveform generators which is an expensive approach when exploring ultra-fast processing speeds. Here we propose the physical generation of clock-free, sub-nanosecond repetitive patterns, with increased intra-pattern diversity and their use as masking sequences. To that end, we investigate numerically a semiconductor laser with a short optical feedback cavity, a well-studied dynamical system that provides a wide diversity of emitted signals. We focus on those operating conditions that lead to a periodic signal generation, with multiple harmonic frequency tones and sub-nanosecond limit cycle dynamics. By tuning the strength of the different frequency tones in the microwave domain, we access a variety of repetitive patterns and sample them in order to obtain the desired masking sequences. Eventually, we apply them in a time delay reservoir computing approach and test them in a nonlinear time-series prediction task. In a performance comparison with masking sequences that originate from random values, we find that only minor compromises are made while significantly reducing the instrumentation requirements of the time delay reservoir computing system.

Entities:  

Year:  2021        PMID: 33758334     DOI: 10.1038/s41598-021-86150-0

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.379


  23 in total

1.  Harnessing nonlinearity: predicting chaotic systems and saving energy in wireless communication.

Authors:  Herbert Jaeger; Harald Haas
Journal:  Science       Date:  2004-04-02       Impact factor: 47.728

2.  Photonic information processing beyond Turing: an optoelectronic implementation of reservoir computing.

Authors:  L Larger; M C Soriano; D Brunner; L Appeltant; J M Gutierrez; L Pesquera; C R Mirasso; I Fischer
Journal:  Opt Express       Date:  2012-01-30       Impact factor: 3.894

3.  Using Digital Masks to Enhance the Bandwidth Tolerance and Improve the Performance of On-Chip Reservoir Computing Systems.

Authors:  Bendix Schneider; Joni Dambre; Peter Bienstman
Journal:  IEEE Trans Neural Netw Learn Syst       Date:  2015-11-23       Impact factor: 10.451

4.  Fiber echo state network analogue for high-bandwidth dual-quadrature signal processing.

Authors:  Mariia Sorokina; Sergey Sergeyev; Sergei Turitsyn
Journal:  Opt Express       Date:  2019-02-04       Impact factor: 3.894

5.  Parallel reservoir computing using optical amplifiers.

Authors:  Kristof Vandoorne; Joni Dambre; David Verstraeten; Benjamin Schrauwen; Peter Bienstman
Journal:  IEEE Trans Neural Netw       Date:  2011-07-29

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

Authors:  Joma Nakayama; Kazutaka Kanno; Atsushi Uchida
Journal:  Opt Express       Date:  2016-04-18       Impact factor: 3.894

7.  Impact of input mask signals on delay-based photonic reservoir computing with semiconductor lasers.

Authors:  Yoma Kuriki; Joma Nakayama; Kosuke Takano; Atsushi Uchida
Journal:  Opt Express       Date:  2018-03-05       Impact factor: 3.894

8.  Constructing optimized binary masks for reservoir computing with delay systems.

Authors:  Lennert Appeltant; Guy Van der Sande; Jan Danckaert; Ingo Fischer
Journal:  Sci Rep       Date:  2014-01-10       Impact factor: 4.379

9.  A Unified Framework for Reservoir Computing and Extreme Learning Machines based on a Single Time-delayed Neuron.

Authors:  S Ortín; M C Soriano; L Pesquera; D Brunner; D San-Martín; I Fischer; C R Mirasso; J M Gutiérrez
Journal:  Sci Rep       Date:  2015-10-08       Impact factor: 4.379

10.  Fully analogue photonic reservoir computer.

Authors:  François Duport; Anteo Smerieri; Akram Akrout; Marc Haelterman; Serge Massar
Journal:  Sci Rep       Date:  2016-03-03       Impact factor: 4.379

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