Literature DB >> 17280024

Persistent chaos in high dimensions.

D J Albers1, J C Sprott, J P Crutchfield.   

Abstract

An extensive statistical survey of universal approximators shows that as the dimension of a typical dissipative dynamical system is increased, the number of positive Lyapunov exponents increases monotonically and the number of parameter windows with periodic behavior decreases. A subset of parameter space remains where noncatastrophic topological change induced by a small parameter variation becomes inevitable. A geometric mechanism depending on dimension and an associated conjecture depict why topological change is expected but not catastrophic, thus providing an explanation of how and why deterministic chaos persists in high dimensions.

Year:  2006        PMID: 17280024     DOI: 10.1103/PhysRevE.74.057201

Source DB:  PubMed          Journal:  Phys Rev E Stat Nonlin Soft Matter Phys        ISSN: 1539-3755


  4 in total

1.  The parameter Houlihan: A solution to high-throughput identifiability indeterminacy for brutally ill-posed problems.

Authors:  David J Albers; Matthew E Levine; Lena Mamykina; George Hripcsak
Journal:  Math Biosci       Date:  2019-08-24       Impact factor: 2.144

2.  Chaos in synthetic microbial communities.

Authors:  Behzad D Karkaria; Angelika Manhart; Alex J H Fedorec; Chris P Barnes
Journal:  PLoS Comput Biol       Date:  2022-10-10       Impact factor: 4.779

3.  Chaos in high-dimensional dissipative dynamical systems.

Authors:  Iaroslav Ispolatov; Vaibhav Madhok; Sebastian Allende; Michael Doebeli
Journal:  Sci Rep       Date:  2015-07-30       Impact factor: 4.379

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

Authors:  Jürgen Eser; Pengsheng Zheng; Jochen Triesch
Journal:  PLoS One       Date:  2014-01-23       Impact factor: 3.240

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.