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

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 n...

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Autores principales: Argyris, Apostolos, Schwind, Janek, Fischer, Ingo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7988145/
https://www.ncbi.nlm.nih.gov/pubmed/33758334
http://dx.doi.org/10.1038/s41598-021-86150-0
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author Argyris, Apostolos
Schwind, Janek
Fischer, Ingo
author_facet Argyris, Apostolos
Schwind, Janek
Fischer, Ingo
author_sort Argyris, Apostolos
collection PubMed
description 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.
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spelling pubmed-79881452021-03-25 Fast physical repetitive patterns generation for masking in time-delay reservoir computing Argyris, Apostolos Schwind, Janek Fischer, Ingo Sci Rep Article 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. Nature Publishing Group UK 2021-03-23 /pmc/articles/PMC7988145/ /pubmed/33758334 http://dx.doi.org/10.1038/s41598-021-86150-0 Text en © The Author(s) 2021 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Argyris, Apostolos
Schwind, Janek
Fischer, Ingo
Fast physical repetitive patterns generation for masking in time-delay reservoir computing
title Fast physical repetitive patterns generation for masking in time-delay reservoir computing
title_full Fast physical repetitive patterns generation for masking in time-delay reservoir computing
title_fullStr Fast physical repetitive patterns generation for masking in time-delay reservoir computing
title_full_unstemmed Fast physical repetitive patterns generation for masking in time-delay reservoir computing
title_short Fast physical repetitive patterns generation for masking in time-delay reservoir computing
title_sort fast physical repetitive patterns generation for masking in time-delay reservoir computing
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7988145/
https://www.ncbi.nlm.nih.gov/pubmed/33758334
http://dx.doi.org/10.1038/s41598-021-86150-0
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