Literature DB >> 23558425

Chaotic Boltzmann machines.

Hideyuki Suzuki1, Jun-ichi Imura, Yoshihiko Horio, Kazuyuki Aihara.   

Abstract

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.

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Year:  2013        PMID: 23558425      PMCID: PMC3617428          DOI: 10.1038/srep01610

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


  18 in total

1.  Equilibrium regained: from nonequilibrium chaos to statistical mechanics.

Authors:  D A Egolf
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2.  Training products of experts by minimizing contrastive divergence.

Authors:  Geoffrey E Hinton
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5.  Computation beyond the turing limit.

Authors:  H T Siegelmann
Journal:  Science       Date:  1995-04-28       Impact factor: 47.728

6.  Beyond the edge of chaos: amplification and temporal integration by recurrent networks in the chaotic regime.

Authors:  T Toyoizumi; L F Abbott
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2011-11-14

Review 7.  Chaos and physiology: deterministic chaos in excitable cell assemblies.

Authors:  T Elbert; W J Ray; Z J Kowalik; J E Skinner; K E Graf; N Birbaumer
Journal:  Physiol Rev       Date:  1994-01       Impact factor: 37.312

Review 8.  Is there chaos in the brain? II. Experimental evidence and related models.

Authors:  Henri Korn; Philippe Faure
Journal:  C R Biol       Date:  2003-09       Impact factor: 1.583

9.  The chaos within Sudoku.

Authors:  Mária Ercsey-Ravasz; Zoltán Toroczkai
Journal:  Sci Rep       Date:  2012-10-11       Impact factor: 4.379

10.  Chaotic Ising-like dynamics in traffic signals.

Authors:  Hideyuki Suzuki; Jun-ichi Imura; Kazuyuki Aihara
Journal:  Sci Rep       Date:  2013-01-24       Impact factor: 4.379

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  4 in total

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Authors:  Suhas Kumar; John Paul Strachan; R Stanley Williams
Journal:  Nature       Date:  2017-08-09       Impact factor: 49.962

2.  Where's the Noise? Key Features of Spontaneous Activity and Neural Variability Arise through Learning in a Deterministic Network.

Authors:  Christoph Hartmann; Andreea Lazar; Bernhard Nessler; Jochen Triesch
Journal:  PLoS Comput Biol       Date:  2015-12-29       Impact factor: 4.475

3.  Nonlinear dynamics analysis of a self-organizing recurrent neural network: chaos waning.

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4.  Hardware emulation of stochastic p-bits for invertible logic.

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Journal:  Sci Rep       Date:  2017-09-08       Impact factor: 4.379

  4 in total

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