fractal property
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2021 ◽  
pp. 126574
Author(s):  
Chao Guo ◽  
Andrew J. Manning ◽  
Sarah Bass ◽  
Leicheng Guo ◽  
Qing He




MENDEL ◽  
2020 ◽  
Vol 26 (1) ◽  
pp. 15-22
Author(s):  
Ivan Zelinka ◽  
Tran Trong Dao

This paper is discussing our new research direction in the Voynich manuscript research. While our previous papers have been dealing with the research that has been based on fractal property analyses or graph properties analyses, where the graph has been constructed from the Voynich manuscript word sequences (Fig. 1), this paper discusses another kind of research on Voynich manuscript. This research is focused on the compassion of the letters or alphabets from Voynich manuscript with another selected alphabets from a different dialect, in that case, dialect from the Indian language. The reason is to point out the possibility that we can identify the origin of the Voynich manuscript alphabets based on the graphical conversion between letters from different dialects. Because this research is a very wide and deep topic, we publish in this paper only basic ideas, simulations and discuss all problems which have been found during those experimentation as well as outlining of the future directions of the research in an outlined way.





2017 ◽  
Vol 66 ◽  
pp. 101-109
Author(s):  
Jiří Fiala ◽  
Jan Hubička ◽  
Yangjing Long ◽  
Jaroslav Nešetřil


2017 ◽  
Vol 90 (1) ◽  
pp. 1-12 ◽  
Author(s):  
Anam Azam ◽  
Muhammad Aqeel ◽  
Salman Ahmad ◽  
Faizan Ahmad


Author(s):  
Sanjukta Krishnagopal ◽  
Judith Lehnert ◽  
Winnie Poel ◽  
Anna Zakharova ◽  
Eckehard Schöll

We investigate complex synchronization patterns such as cluster synchronization and partial amplitude death in networks of coupled Stuart–Landau oscillators with fractal connectivities. The study of fractal or self-similar topology is motivated by the network of neurons in the brain. This fractal property is well represented in hierarchical networks, for which we present three different models. In addition, we introduce an analytical eigensolution method and provide a comprehensive picture of the interplay of network topology and the corresponding network dynamics, thus allowing us to predict the dynamics of arbitrarily large hierarchical networks simply by analysing small network motifs. We also show that oscillation death can be induced in these networks, even if the coupling is symmetric, contrary to previous understanding of oscillation death. Our results show that there is a direct correlation between topology and dynamics: hierarchical networks exhibit the corresponding hierarchical dynamics. This helps bridge the gap between mesoscale motifs and macroscopic networks. This article is part of the themed issue ‘Horizons of cybernetical physics’.





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