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

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...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Apostolos Argyris, Janek Schwind, Ingo Fischer
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/69481108b2804b9c8465743afaa932b5
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:69481108b2804b9c8465743afaa932b5
record_format	dspace
spelling	oai:doaj.org-article:69481108b2804b9c8465743afaa932b52021-12-02T16:35:56ZFast physical repetitive patterns generation for masking in time-delay reservoir computing10.1038/s41598-021-86150-02045-2322https://doaj.org/article/69481108b2804b9c8465743afaa932b52021-03-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-86150-0https://doaj.org/toc/2045-2322Abstract 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.Apostolos ArgyrisJanek SchwindIngo FischerNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Apostolos Argyris Janek Schwind Ingo Fischer Fast physical repetitive patterns generation for masking in time-delay reservoir computing
description	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.
format	article
author	Apostolos Argyris Janek Schwind Ingo Fischer
author_facet	Apostolos Argyris Janek Schwind Ingo Fischer
author_sort	Apostolos Argyris
title	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_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_sort	fast physical repetitive patterns generation for masking in time-delay reservoir computing
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/69481108b2804b9c8465743afaa932b5
work_keys_str_mv	AT apostolosargyris fastphysicalrepetitivepatternsgenerationformaskingintimedelayreservoircomputing AT janekschwind fastphysicalrepetitivepatternsgenerationformaskingintimedelayreservoircomputing AT ingofischer fastphysicalrepetitivepatternsgenerationformaskingintimedelayreservoircomputing
_version_	1718383694888042496

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

Ejemplares similares