A statistical approach to the identification of diploid cellular automata based on incomplete observations.

Diploid cellular automata Parameter estimation Stochastic cellular automata System identification

Journal

Bio Systems
ISSN: 1872-8324
Titre abrégé: Biosystems
Pays: Ireland
ID NLM: 0430773

Informations de publication

Date de publication:
Dec 2019
Historique:
received: 02 04 2018
revised: 30 03 2019
accepted: 26 05 2019
pubmed: 4 6 2019
medline: 28 5 2020
entrez: 2 6 2019
Statut: ppublish

Résumé

In this paper, the identification problem of diploid cellular automata is considered, in which, based on a series of incomplete observations, the underlying cellular automaton rules and the states of missing cell states are to be uncovered. An algorithm for identifying the rule, based on a statistical parameter estimation method using a normal distribution approximation, is presented. In addition, an algorithm for filling the missing cell states is formulated. The accuracy of these methods is examined in a series of computational experiments.

Identifiants

pubmed: 31152774
pii: S0303-2647(18)30128-X
doi: 10.1016/j.biosystems.2019.103976
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

103976

Informations de copyright

Copyright © 2019 Elsevier B.V. All rights reserved.

Auteurs

Witold Bołt (W)

Systems Research Institute, Polish Academy of Sciences, Newelska St. 6, 01-447 Warsaw, Poland; KERMIT, Department of Data Analysis and Mathematical Modelling, Ghent University, B-9000 Ghent, Belgium. Electronic address: witold.bolt@hope.art.pl.

Aleksander Bołt (A)

Institute of Mathematics, Faculty of Mathematics, Physics and Informatics, University of Gdańsk, 80-308 Gdańsk, Poland.

Barbara Wolnik (B)

Institute of Mathematics, Faculty of Mathematics, Physics and Informatics, University of Gdańsk, 80-308 Gdańsk, Poland.

Jan M Baetens (JM)

KERMIT, Department of Data Analysis and Mathematical Modelling, Ghent University, B-9000 Ghent, Belgium.

Bernard De Baets (B)

KERMIT, Department of Data Analysis and Mathematical Modelling, Ghent University, B-9000 Ghent, Belgium.

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Classifications MeSH