A method for analyzing deterministic dynamical systems is presented. New measures of complexity are proposed, based on fluctuation in net information gain and its dependence on system size. These measures are applied to one-dimensional cellular automata and shown to be useful in selecting rules that support slow-moving gliders in quiescent backgrounds.
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Univ New S Wales, ADFA, Sch Engn & Informat Technol, Bioinformat Res Grp, Canberra, ACT 2600, AustraliaUniv New S Wales, ADFA, Sch Engn & Informat Technol, Bioinformat Res Grp, Canberra, ACT 2600, Australia
El-Fiqi, Heba Z.
Pham, Tuan D.
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Univ New S Wales, ADFA, Sch Engn & Informat Technol, Bioinformat Res Grp, Canberra, ACT 2600, AustraliaUniv New S Wales, ADFA, Sch Engn & Informat Technol, Bioinformat Res Grp, Canberra, ACT 2600, Australia
Pham, Tuan D.
Hattori, Haroldo T.
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Univ New S Wales, ADFA, Sch Engn & Informat Technol, Bioinformat Res Grp, Canberra, ACT 2600, AustraliaUniv New S Wales, ADFA, Sch Engn & Informat Technol, Bioinformat Res Grp, Canberra, ACT 2600, Australia
Hattori, Haroldo T.
Crane, Denis I.
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Griffith Univ, Sch Bimol & Phys Sci, Eskitis Inst Cell & Mol Therapies, Nathan, Qld 4111, AustraliaUniv New S Wales, ADFA, Sch Engn & Informat Technol, Bioinformat Res Grp, Canberra, ACT 2600, Australia
Crane, Denis I.
2009 INTERNATIONAL SYMPOSIUM ON COMPUTATIONAL MODELS FOR LIFE SCIENCES (CMLS '09),
2010,
1210
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