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Towards Embedded Computation with Building Materials

We present results showing the capability of concrete-based information processing substrate in the signal classification task in accordance with in materio computing paradigm. As the Reservoir Computing is a suitable model for describing embedded in materio computation, we propose that this type of...

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Detalles Bibliográficos
Autores principales: Przyczyna, Dawid, Suchecki, Maciej, Adamatzky, Andrew, Szaciłowski, Konrad
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8038044/
https://www.ncbi.nlm.nih.gov/pubmed/33807438
http://dx.doi.org/10.3390/ma14071724
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author Przyczyna, Dawid
Suchecki, Maciej
Adamatzky, Andrew
Szaciłowski, Konrad
author_facet Przyczyna, Dawid
Suchecki, Maciej
Adamatzky, Andrew
Szaciłowski, Konrad
author_sort Przyczyna, Dawid
collection PubMed
description We present results showing the capability of concrete-based information processing substrate in the signal classification task in accordance with in materio computing paradigm. As the Reservoir Computing is a suitable model for describing embedded in materio computation, we propose that this type of presented basic construction unit can be used as a source for “reservoir of states” necessary for simple tuning of the readout layer. We present an electrical characterization of the set of samples with different additive concentrations followed by a dynamical analysis of selected specimens showing fingerprints of memfractive properties. As part of dynamic analysis, several fractal dimensions and entropy parameters for the output signal were analyzed to explore the richness of the reservoir configuration space. In addition, to investigate the chaotic nature and self-affinity of the signal, Lyapunov exponents and Detrended Fluctuation Analysis exponents were calculated. Moreover, on the basis of obtained parameters, classification of the signal waveform shapes can be performed in scenarios explicitly tuned for a given device terminal.
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spelling pubmed-80380442021-04-12 Towards Embedded Computation with Building Materials Przyczyna, Dawid Suchecki, Maciej Adamatzky, Andrew Szaciłowski, Konrad Materials (Basel) Article We present results showing the capability of concrete-based information processing substrate in the signal classification task in accordance with in materio computing paradigm. As the Reservoir Computing is a suitable model for describing embedded in materio computation, we propose that this type of presented basic construction unit can be used as a source for “reservoir of states” necessary for simple tuning of the readout layer. We present an electrical characterization of the set of samples with different additive concentrations followed by a dynamical analysis of selected specimens showing fingerprints of memfractive properties. As part of dynamic analysis, several fractal dimensions and entropy parameters for the output signal were analyzed to explore the richness of the reservoir configuration space. In addition, to investigate the chaotic nature and self-affinity of the signal, Lyapunov exponents and Detrended Fluctuation Analysis exponents were calculated. Moreover, on the basis of obtained parameters, classification of the signal waveform shapes can be performed in scenarios explicitly tuned for a given device terminal. MDPI 2021-03-31 /pmc/articles/PMC8038044/ /pubmed/33807438 http://dx.doi.org/10.3390/ma14071724 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Przyczyna, Dawid
Suchecki, Maciej
Adamatzky, Andrew
Szaciłowski, Konrad
Towards Embedded Computation with Building Materials
title Towards Embedded Computation with Building Materials
title_full Towards Embedded Computation with Building Materials
title_fullStr Towards Embedded Computation with Building Materials
title_full_unstemmed Towards Embedded Computation with Building Materials
title_short Towards Embedded Computation with Building Materials
title_sort towards embedded computation with building materials
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8038044/
https://www.ncbi.nlm.nih.gov/pubmed/33807438
http://dx.doi.org/10.3390/ma14071724
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