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Chaotic Boltzmann machines
The chaotic Boltzmann machine proposed in this paper is a chaotic pseudo-billiard system that works as a Boltzmann machine. Chaotic Boltzmann machines are shown numerically to have computing abilities comparable to conventional (stochastic) Boltzmann machines. Since no randomness is required, effici...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3617428/ https://www.ncbi.nlm.nih.gov/pubmed/23558425 http://dx.doi.org/10.1038/srep01610 |
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author | Suzuki, Hideyuki Imura, Jun-ichi Horio, Yoshihiko Aihara, Kazuyuki |
author_facet | Suzuki, Hideyuki Imura, Jun-ichi Horio, Yoshihiko Aihara, Kazuyuki |
author_sort | Suzuki, Hideyuki |
collection | PubMed |
description | The chaotic Boltzmann machine proposed in this paper is a chaotic pseudo-billiard system that works as a Boltzmann machine. Chaotic Boltzmann machines are shown numerically to have computing abilities comparable to conventional (stochastic) Boltzmann machines. Since no randomness is required, efficient hardware implementation is expected. Moreover, the ferromagnetic phase transition of the Ising model is shown to be characterised by the largest Lyapunov exponent of the proposed system. In general, a method to relate probabilistic models to nonlinear dynamics by derandomising Gibbs sampling is presented. |
format | Online Article Text |
id | pubmed-3617428 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-36174282013-04-05 Chaotic Boltzmann machines Suzuki, Hideyuki Imura, Jun-ichi Horio, Yoshihiko Aihara, Kazuyuki Sci Rep Article The chaotic Boltzmann machine proposed in this paper is a chaotic pseudo-billiard system that works as a Boltzmann machine. Chaotic Boltzmann machines are shown numerically to have computing abilities comparable to conventional (stochastic) Boltzmann machines. Since no randomness is required, efficient hardware implementation is expected. Moreover, the ferromagnetic phase transition of the Ising model is shown to be characterised by the largest Lyapunov exponent of the proposed system. In general, a method to relate probabilistic models to nonlinear dynamics by derandomising Gibbs sampling is presented. Nature Publishing Group 2013-04-05 /pmc/articles/PMC3617428/ /pubmed/23558425 http://dx.doi.org/10.1038/srep01610 Text en Copyright © 2013, Macmillan Publishers Limited. All rights reserved http://creativecommons.org/licenses/by/3.0/ This work is licensed under a Creative Commons Attribution 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/3.0/ |
spellingShingle | Article Suzuki, Hideyuki Imura, Jun-ichi Horio, Yoshihiko Aihara, Kazuyuki Chaotic Boltzmann machines |
title | Chaotic Boltzmann machines |
title_full | Chaotic Boltzmann machines |
title_fullStr | Chaotic Boltzmann machines |
title_full_unstemmed | Chaotic Boltzmann machines |
title_short | Chaotic Boltzmann machines |
title_sort | chaotic boltzmann machines |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3617428/ https://www.ncbi.nlm.nih.gov/pubmed/23558425 http://dx.doi.org/10.1038/srep01610 |
work_keys_str_mv | AT suzukihideyuki chaoticboltzmannmachines AT imurajunichi chaoticboltzmannmachines AT horioyoshihiko chaoticboltzmannmachines AT aiharakazuyuki chaoticboltzmannmachines |